Offline voice control

ABSTRACT

As noted above, example techniques relate to offline voice control. A local voice input engine may process voice inputs locally when processing voice inputs via a cloud-based voice assistant service is not possible. Some techniques involve local (on-device) voice-assisted set-up of a cloud-based voice assistant service. Further example techniques involve local voice-assisted troubleshooting the cloud-based voice assistant service. Other techniques relate to interactions between local and cloud-based processing of voice inputs on a device that supports both local and cloud-based processing.

FIELD OF THE DISCLOSURE

The present technology relates to consumer goods and, more particularly,to methods, systems, products, features, services, and other elementsdirected to voice-assisted control of media playback systems or someaspect thereof.

BACKGROUND

Options for accessing and listening to digital audio in an out-loudsetting were limited until in 2002, when SONOS, Inc. began developmentof a new type of playback system. Sonos then filed one of its firstpatent applications in 2003, entitled “Method for Synchronizing AudioPlayback between Multiple Networked Devices,” and began offering itsfirst media playback systems for sale in 2005. The Sonos Wireless HomeSound System enables people to experience music from many sources viaone or more networked playback devices. Through a software controlapplication installed on a controller (e.g., smartphone, tablet,computer, voice input device), one can play what she wants in any roomhaving a networked playback device. Media content (e.g., songs,podcasts, video sound) can be streamed to playback devices such thateach room with a playback device can play back corresponding differentmedia content. In addition, rooms can be grouped together forsynchronous playback of the same media content, and/or the same mediacontent can be heard in all rooms synchronously.

BRIEF DESCRIPTION OF THE DRAWINGS

Features, aspects, and advantages of the presently disclosed technologymay be better understood with regard to the following description,appended claims, and accompanying drawings where:

Features, aspects, and advantages of the presently disclosed technologymay be better understood with regard to the following description,appended claims, and accompanying drawings, as listed below. A personskilled in the relevant art will understand that the features shown inthe drawings are for purposes of illustrations, and variations,including different and/or additional features and arrangements thereof,are possible.

FIG. 1A is a partial cutaway view of an environment having a mediaplayback system configured in accordance with aspects of the disclosedtechnology.

FIG. 1B is a schematic diagram of the media playback system of FIG. 1Aand one or more networks.

FIG. 2A is a functional block diagram of an example playback device.

FIG. 2B is an isometric diagram of an example housing of the playbackdevice of FIG. 2A.

FIG. 2C is a diagram of an example voice input.

FIG. 2D is a graph depicting an example sound specimen in accordancewith aspects of the disclosure.

FIGS. 3A, 3B, 3C, 3D and 3E are diagrams showing example playback deviceconfigurations in accordance with aspects of the disclosure.

FIG. 4 is a functional block diagram of an example controller device inaccordance with aspects of the disclosure.

FIGS. 5A and 5B are controller interfaces in accordance with aspects ofthe disclosure.

FIG. 6 is a message flow diagram of a media playback system.

FIG. 7A is a functional block diagram of an example network microphonedevice.

FIG. 7B is an isometric diagram of the example network microphonedevice.

FIG. 7C is a functional block diagram of certain components of theexample network microphone device in accordance with aspects of thedisclosure.

FIGS. 8A, 8B, 8C, 8D, 8E, and 8F illustrate example conversationsbetween a user and the example network microphone device.

FIG. 9 is a schematic diagram illustrating the example networkmicrophone device while paired with an example network device.

FIG. 10 is a schematic diagram illustrating an example media playbacksystem and cloud network in accordance with aspects of the disclosure.

FIGS. 11A, 11B, 11C, and 11D show exemplary output of an example NMDconfigured in accordance with aspects of the disclosure.

FIG. 12 is a flow diagram of an example method to perform offline voiceprocessing in accordance with aspects of the disclosure.

The drawings are for purposes of illustrating example embodiments, butit should be understood that the inventions are not limited to thearrangements and instrumentality shown in the drawings. In the drawings,identical reference numbers identify at least generally similarelements. To facilitate the discussion of any particular element, themost significant digit or digits of any reference number refers to theFigure in which that element is first introduced. For example, element103 a is first introduced and discussed with reference to FIG. 1A.

DETAILED DESCRIPTION I. Overview

Example techniques described herein involve offline voice control usinga networked microphone device (“NMD”). An NMD is a networked computingdevice that typically includes an arrangement of microphones, such as amicrophone array, that is configured to detect sound present in theNMD's environment. NMDs may facilitate voice control of smart homedevices, such as wireless audio playback devices, illumination devices,appliances, and home-automation devices (e.g., thermostats, door locks,etc.). NMDs may also be used to query a cloud-based VAS for informationsuch as search queries, news, weather, and the like.

Example NMDs disclosed herein support both cloud-based and localprocessing of voice inputs. Generally, cloud-based VAS(s) are relativelymore capable than local (“on-device”) voice input engines. Inparticular, in contrast to a natural language unit (NLU) implemented inone or more cloud servers that is capable of recognizing a wide varietyof voice inputs, it is generally impracticable for local NLUs torecognize voice inputs at the level of scale of a cloud-based NLU. Forexample, a local NLU implemented by an NMD may be capable of recognizinga relatively smaller library of keywords (e.g., 10,000 words andphrases). Further, the cloud-based VAS may support additional featuresrelative to a local NLU, such as the ability to support a greater breathof features at the same time.

While cloud-based VASs are relatively more capable than local voiceinput engines, processing via a cloud-based VAS may be unavailable insome circumstances. For instance, a cloud-based VAS is unusable wheneither the NMD or the servers of the VAS are offline. As anotherexample, a cloud-based VAS may require that an NMD be set-up for thecloud-based VAS before the NMD can use the cloud-based VAS to processvoice inputs.

More particularly, to begin using a cloud-based VAS on an NMD, a user istypically required to perform a VAS set-up procedure using a smartphoneapp or other graphical user interface (“GUI”). This set-up procedure mayinvolve connecting the NMD to a wireless local area network (“LAN”) soas to establish an Internet connection to servers of a cloud-based VAS.The VAS set-up procedure may also involve associating a user account ofthe cloud-based VAS with the NMD, among other possible steps.

In example implementations, a local voice input pipeline ispre-configured to process voice inputs using the local NLU before theNMD is configured with a cloud-based VAS. For instance, an example NMDmay be pre-configured during manufacturing to start listening forcertain voice inputs (e.g., keywords relating to set-up) when the NMD ispowered on. Alternatively, after being powered-on (e.g., for the firsttime), the NMD may output an audible prompt (and/or anothernotification, such as a push notification on a mobile device) thatinforms the user that local (i.e., offline) voice processing isavailable and asks the user if they would like to enable suchprocessing. Upon receiving a voice input representing a command toenable local voice processing, the NMD enables the local voice inputpipeline to process voice inputs locally.

Since the local voice input pipeline is able to process voice inputsoffline, the local voice input engine may facilitate set-up of the NMD,including set-up of one or more cloud-based VAS(s). In contrast, asnoted above, a cloud-based VAS requires some set-up or otherconfiguration before use. Facilitating set-up may take the form of aseries of pre-recorded audible prompts asking the user for input. Aftereach audible prompt asking for input, the NMD may process the voiceresponse of the user using the local voice input pipeline. In contrastto a cloud-based VAS, which is triggered based on a wake word, the localvoice input pipeline may initiate the “conversation” with the user byprompting the user during set-up.

For instance, during set-up, a NMD may output audible prompts to providenetwork set-up information, such as the name of the wireless LAN (e.g.,a service set identifier (“SSID”)) and/or a wireless password. Further,the NMD may output audible prompts to provide account information forone or more cloud-based VAS(s) to facilitate configuration of thoseservices with the NMD using voice input, as an alternative to using aGUI. After outputting an audible prompt, the NMD may listen for a voiceresponse by the user and then determine an intent of the voice response.Through these voice inputs, the NMD may obtain set-up information forone or more cloud-based VAS(s) without necessarily requiring the userusing a smartphone app or other GUI to set-up the cloud-based VAS.

The local voice input pipeline may also facilitate troubleshooting. Insome circumstances, a cloud-based VAS may fail to provide a response toa voice input, perhaps because the service is down or because theInternet connection of the NMD has been lost. In such cases, the NMD maydetect such a failure, and initiate a troubleshooting procedure. Forinstance, the NMD may test its Internet connection (e.g., by pinging oneor more high availability servers, e.g., a public DNS server). The NMDmay also prompt the user to perform one or more troubleshooting actions,and then to provide a voice response indicating the result of theaction. In other examples, the NMD may monitor the connection status ofthe cloud-based VAS and proactively inform the user when the cloud-basedVAS is unavailable, e.g., when a VAS wake-word is spoken.

Moreover, some users are apprehensive of sending their voice data to acloud-based VAS for privacy reasons. One possible advantage of aprocessing voice inputs via a local NLU is increased privacy. Byprocessing voice utterances locally, a user may avoid transmitting voicerecordings to the cloud (e.g., to servers of a voice assistant service).Further, in some implementations, the NMD may use a local area networkto discover playback devices and/or smart devices connected to thenetwork, which may avoid providing personal data relating to a user'shome to the cloud. Also, the user's preferences and customizations mayremain local to the NMD(s) in the household, perhaps only using thecloud as an optional backup. Accordingly, some users might not enableprocessing via a cloud-based VAS and instead rely on the local voiceinput pipeline.

In example implementations, the local voice input pipeline may operatein one of two modes, referred to herein as a set-up mode and anoperating mode. In the set-up mode, the local voice input pipeline isconfigured to detect a subset of keywords from a library of a local NLU.These keywords may include commands and keywords related to set-up ofthe NMD. Conversely, in the operating mode, the local voice inputpipeline is configured to detect additional keywords, which may includeadditional commands as well as personalized keywords (e.g., namesassigned to the user's devices).

As noted above, example techniques relate to offline voice control. Anexample implementation involves a network microphone device includingone or more microphones, a network interface, one or more processors, atleast one speaker, one or more processor and data storage having storedtherein instructions executable by the one or more processors. While alocal voice input pipeline is in a set-up mode, the network microphonedevice monitors, via the local voice input pipeline, a sound data streamfrom the one or more microphones for local keywords from a local naturallanguage unit library of the local voice input pipeline. The networkmicrophone device generates a local wake-word event corresponding to afirst voice input when the local voice input pipeline detects sound datamatching one or more particular local keywords in a first portion of thesound data stream and determines, via a local natural language unit ofthe local voice input pipeline, an intent based on the one or moreparticular local keywords of the first voice input. The determinedintent represents a command to configure a voice assistant service onthe playback device. Based on the determined intent, the networkedmicrophone device outputs, via the at least one speaker, one or moreaudible prompts to configure a VAS wake-word engine for one or morevoice assistant services. After the VAS wake-word engine is configuredfor a particular voice assistant service, the networked microphonedevice monitors, via the VAS wake-word engine, the sound data streamfrom the one or more microphones for one or more VAS wake words of theparticular voice assistant service. The networked microphone devicegenerates a VAS wake-word event corresponding to a second voice inputwhen the VAS wake-word engine detects sound data matching a particularVAS wake word in a second portion of the sound data stream. When a VASwake word event is generated, the playback device streams sound datarepresenting the second voice input to one or more servers of theparticular voice assistant service. The networked microphone devicedetects a failure by the particular voice assistant service to provide aresponse to the second voice input. Based on detecting the failure, thenetworked microphone device outputs, via the at least one speaker, anaudible troubleshooting prompt indicating at least one of: (a) one ormore issues causing the failure or (b) one or more troubleshootingactions to correct the one or more issues causing the failure. Afterplaying back the audible troubleshooting prompt, the networkedmicrophone device monitors, via the local voice input pipeline, thesound data stream from the one or more microphones for a voice inputresponse to the audible troubleshooting prompt. The networked microphonedevice determines, via the local natural language unit, an intent of thevoice input response to the audible troubleshooting prompt and performsone or more operations according to the determined intent of the voiceinput response to the audible troubleshooting prompt.

While some embodiments described herein may refer to functions performedby given actors, such as “users” and/or other entities, it should beunderstood that this description is for purposes of explanation only.The claims should not be interpreted to require action by any suchexample actor unless explicitly required by the language of the claimsthemselves.

Moreover, some functions are described herein as being performed “basedon” or “in response to” another element or function. “Based on” shouldbe understood that one element or function is related to anotherfunction or element. “In response to” should be understood that oneelement or function is a necessary result of another function orelement. For the sake of brevity, functions are generally described asbeing based on another function when a functional link exists; however,such disclosure should be understood as disclosing either type offunctional relationship.

II. Example Operation Environment

FIGS. 1A and 1B illustrate an example configuration of a media playbacksystem 100 (or “MPS 100”) in which one or more embodiments disclosedherein may be implemented. Referring first to FIG. 1A, the MPS 100 asshown is associated with an example home environment having a pluralityof rooms and spaces, which may be collectively referred to as a “homeenvironment,” “smart home,” or “environment 101.” The environment 101comprises a household having several rooms, spaces, and/or playbackzones, including a master bathroom 101 a, a master bedroom 101 b,(referred to herein as “Nick's Room”), a second bedroom 101 c, a familyroom or den 101 d, an office 101 e, a living room 101 f, a dining room101 g, a kitchen 101 h, and an outdoor patio 101 i. While certainembodiments and examples are described below in the context of a homeenvironment, the technologies described herein may be implemented inother types of environments. In some embodiments, for example, the MPS100 can be implemented in one or more commercial settings (e.g., arestaurant, mall, airport, hotel, a retail or other store), one or morevehicles (e.g., a sports utility vehicle, bus, car, a ship, a boat, anairplane), multiple environments (e.g., a combination of home andvehicle environments), and/or another suitable environment wheremulti-zone audio may be desirable.

Within these rooms and spaces, the MPS 100 includes one or morecomputing devices. Referring to FIGS. 1A and 1B together, such computingdevices can include playback devices 102 (identified individually asplayback devices 102 a-102 o), network microphone devices 103(identified individually as “NMDs” 103 a-102 i), and controller devices104 a and 104 b (collectively “controller devices 104”). Referring toFIG. 1B, the home environment may include additional and/or othercomputing devices, including local network devices, such as one or moresmart illumination devices 108 (FIG. 1B), a smart thermostat 110, and alocal computing device 105 (FIG. 1A). In embodiments described below,one or more of the various playback devices 102 may be configured asportable playback devices, while others may be configured as stationaryplayback devices. For example, the headphones 102 o (FIG. 1B) are aportable playback device, while the playback device 102 d on thebookcase may be a stationary device. As another example, the playbackdevice 102 c on the Patio may be a battery-powered device, which mayallow it to be transported to various areas within the environment 101,and outside of the environment 101, when it is not plugged in to a walloutlet or the like.

With reference still to FIG. 1B, the various playback, networkmicrophone, and controller devices 102, 103, and 104 and/or othernetwork devices of the MPS 100 may be coupled to one another viapoint-to-point connections and/or over other connections, which may bewired and/or wireless, via a network 111, such as a LAN including anetwork router 109. For example, the playback device 102 j in the Den101 d (FIG. 1A), which may be designated as the “Left” device, may havea point-to-point connection with the playback device 102 a, which isalso in the Den 101 d and may be designated as the “Right” device. In arelated embodiment, the Left playback device 102 j may communicate withother network devices, such as the playback device 102 b, which may bedesignated as the “Front” device, via a point-to-point connection and/orother connections via the NETWORK 111.

As further shown in FIG. 1B, the MPS 100 may be coupled to one or moreremote computing devices 106 via a wide area network (“WAN”) 107. Insome embodiments, each remote computing device 106 may take the form ofone or more cloud servers. The remote computing devices 106 may beconfigured to interact with computing devices in the environment 101 invarious ways. For example, the remote computing devices 106 may beconfigured to facilitate streaming and/or controlling playback of mediacontent, such as audio, in the home environment 101.

In some implementations, the various playback devices, NMDs, and/orcontroller devices 102-104 may be communicatively coupled to at leastone remote computing device associated with a VAS and at least oneremote computing device associated with a media content service (“MCS”).For instance, in the illustrated example of FIG. 1B, remote computingdevices 106 are associated with a VAS 190 and remote computing devices106 b are associated with an MCS 192. Although only a single VAS 190 anda single MCS 192 are shown in the example of FIG. 1B for purposes ofclarity, the MPS 100 may be coupled to multiple, different VASes and/orMCSes. In some implementations, VASes may be operated by one or more ofAMAZON, GOOGLE, APPLE, MICROSOFT, SONOS or other voice assistantproviders. In some implementations, MCSes may be operated by one or moreof SPOTIFY, PANDORA, AMAZON MUSIC, or other media content services.

As further shown in FIG. 1B, the remote computing devices 106 furtherinclude remote computing device 106 c configured to perform certainoperations, such as remotely facilitating media playback functions,managing device and system status information, directing communicationsbetween the devices of the MPS 100 and one or multiple VASes and/orMCSes, among other operations. In one example, the remote computingdevices 106 c provide cloud servers for one or more SONOS Wireless HiFiSystems.

In various implementations, one or more of the playback devices 102 maytake the form of or include an on-board (e.g., integrated) networkmicrophone device. For example, the playback devices 102 a-e include orare otherwise equipped with corresponding NMDs 103 a-e, respectively. Aplayback device that includes or is equipped with an NMD may be referredto herein interchangeably as a playback device or an NMD unlessindicated otherwise in the description. In some cases, one or more ofthe NMDs 103 may be a stand-alone device. For example, the NMDs 103 fand 103 g may be stand-alone devices. A stand-alone NMD may omitcomponents and/or functionality that is typically included in a playbackdevice, such as a speaker or related electronics. For instance, in suchcases, a stand-alone NMD may not produce audio output or may producelimited audio output (e.g., relatively low-quality audio output).

The various playback and network microphone devices 102 and 103 of theMPS 100 may each be associated with a unique name, which may be assignedto the respective devices by a user, such as during setup of one or moreof these devices. For instance, as shown in the illustrated example ofFIG. 1B, a user may assign the name “Bookcase” to playback device 102 dbecause it is physically situated on a bookcase. Similarly, the NMD 103f may be assigned the named “Island” because it is physically situatedon an island countertop in the Kitchen 101 h (FIG. 1A). Some playbackdevices may be assigned names according to a zone or room, such as theplayback devices 102 e, 1021, 102 m, and 102 n, which are named“Bedroom,” “Dining Room,” “Living Room,” and “Office,” respectively.Further, certain playback devices may have functionally descriptivenames. For example, the playback devices 102 a and 102 b are assignedthe names “Right” and “Front,” respectively, because these two devicesare configured to provide specific audio channels during media playbackin the zone of the Den 101 d (FIG. 1A). The playback device 102 c in thePatio may be named portable because it is battery-powered and/or readilytransportable to different areas of the environment 101. Other namingconventions are possible.

As discussed above, an NMD may detect and process sound from itsenvironment, such as sound that includes background noise mixed withspeech spoken by a person in the NMD's vicinity. For example, as soundsare detected by the NMD in the environment, the NMD may process thedetected sound to determine if the sound includes speech that containsvoice input intended for the NMD and ultimately a particular VAS. Forexample, the NMD may identify whether speech includes a wake wordassociated with a particular VAS.

In the illustrated example of FIG. 1B, the NMDs 103 are configured tointeract with the VAS 190 over a network via the network 111 and therouter 109. Interactions with the VAS 190 may be initiated, for example,when an NMD identifies in the detected sound a potential wake word. Theidentification causes a wake-word event, which in turn causes the NMD tobegin transmitting detected-sound data to the VAS 190. In someimplementations, the various local network devices 102-105 (FIG. 1A)and/or remote computing devices 106 c of the MPS 100 may exchangevarious feedback, information, instructions, and/or related data withthe remote computing devices associated with the selected VAS. Suchexchanges may be related to or independent of transmitted messagescontaining voice inputs. In some embodiments, the remote computingdevice(s) and the MPS 100 may exchange data via communication paths asdescribed herein and/or using a metadata exchange channel as describedin U.S. application Ser. No. 15/438,749 filed Feb. 21, 2017, and titled“Voice Control of a Media Playback System,” which is herein incorporatedby reference in its entirety.

Upon receiving the stream of sound data, the VAS 190 determines if thereis voice input in the streamed data from the NMD, and if so the VAS 190will also determine an underlying intent in the voice input. The VAS 190may next transmit a response back to the MPS 100, which can includetransmitting the response directly to the NMD that caused the wake-wordevent. The response is typically based on the intent that the VAS 190determined was present in the voice input. As an example, in response tothe VAS 190 receiving a voice input with an utterance to “Play Hey Judeby The Beatles,” the VAS 190 may determine that the underlying intent ofthe voice input is to initiate playback and further determine thatintent of the voice input is to play the particular song “Hey Jude.”After these determinations, the VAS 190 may transmit a command to aparticular MCS 192 to retrieve content (i.e., the song “Hey Jude”), andthat MCS 192, in turn, provides (e.g., streams) this content directly tothe MPS 100 or indirectly via the VAS 190. In some implementations, theVAS 190 may transmit to the MPS 100 a command that causes the MPS 100itself to retrieve the content from the MCS 192.

In certain implementations, NMDs may facilitate arbitration amongst oneanother when voice input is identified in speech detected by two or moreNMDs located within proximity of one another. For example, theNMD-equipped playback device 102 d in the environment 101 (FIG. 1A) isin relatively close proximity to the NMD-equipped Living Room playbackdevice 102 m, and both devices 102 d and 102 m may at least sometimesdetect the same sound. In such cases, this may require arbitration as towhich device is ultimately responsible for providing detected-sound datato the remote VAS. Examples of arbitrating between NMDs may be found,for example, in previously referenced U.S. application Ser. No.15/438,749.

In certain implementations, an NMD may be assigned to, or otherwiseassociated with, a designated or default playback device that may notinclude an NMD. For example, the Island NMD 103 f in the Kitchen 101 h(FIG. 1A) may be assigned to the Dining Room playback device 102 l,which is in relatively close proximity to the Island NMD 103 f Inpractice, an NMD may direct an assigned playback device to play audio inresponse to a remote VAS receiving a voice input from the NMD to playthe audio, which the NMD might have sent to the VAS in response to auser speaking a command to play a certain song, album, playlist, etc.Additional details regarding assigning NMDs and playback devices asdesignated or default devices may be found, for example, in previouslyreferenced U.S. patent application Ser. No. 15/438,749.

Further aspects relating to the different components of the example MPS100 and how the different components may interact to provide a user witha media experience may be found in the following sections. Whilediscussions herein may generally refer to the example MPS 100,technologies described herein are not limited to applications within,among other things, the home environment described above. For instance,the technologies described herein may be useful in other homeenvironment configurations comprising more or fewer of any of theplayback, network microphone, and/or controller devices 102-104. Forexample, the technologies herein may be utilized within an environmenthaving a single playback device 102 and/or a single NMD 103. In someexamples of such cases, the NETWORK 111 (FIG. 1B) may be eliminated andthe single playback device 102 and/or the single NMD 103 may communicatedirectly with the remote computing devices 106-d. In some embodiments, atelecommunication network (e.g., an LTE network, a 5G network, etc.) maycommunicate with the various playback, network microphone, and/orcontroller devices 102-104 independent of a LAN.

a. Example Playback & Network Microphone Devices

FIG. 2A is a functional block diagram illustrating certain aspects ofone of the playback devices 102 of the MPS 100 of FIGS. 1A and 1B. Asshown, the playback device 102 includes various components, each ofwhich is discussed in further detail below, and the various componentsof the playback device 102 may be operably coupled to one another via asystem bus, communication network, or some other connection mechanism.In the illustrated example of FIG. 2A, the playback device 102 may bereferred to as an “NMD-equipped” playback device because it includescomponents that support the functionality of an NMD, such as one of theNMDs 103 shown in FIG. 1A.

As shown, the playback device 102 includes at least one processor 212,which may be a clock-driven computing component configured to processinput data according to instructions stored in memory 213. The memory213 may be a tangible, non-transitory, computer-readable mediumconfigured to store instructions that are executable by the processor212. For example, the memory 213 may be data storage that can be loadedwith software code 214 that is executable by the processor 212 toachieve certain functions.

In one example, these functions may involve the playback device 102retrieving audio data from an audio source, which may be anotherplayback device. In another example, the functions may involve theplayback device 102 sending audio data, detected-sound data (e.g.,corresponding to a voice input), and/or other information to anotherdevice on a network via at least one network interface 224. In yetanother example, the functions may involve the playback device 102causing one or more other playback devices to synchronously playbackaudio with the playback device 102. In yet a further example, thefunctions may involve the playback device 102 facilitating being pairedor otherwise bonded with one or more other playback devices to create amulti-channel audio environment. Numerous other example functions arepossible, some of which are discussed below.

As just mentioned, certain functions may involve the playback device 102synchronizing playback of audio content with one or more other playbackdevices. During synchronous playback, a listener may not perceivetime-delay differences between playback of the audio content by thesynchronized playback devices. U.S. Pat. No. 8,234,395 filed on Apr. 4,2004, and titled “System and method for synchronizing operations among aplurality of independently clocked digital data processing devices,”which is hereby incorporated by reference in its entirety, provides inmore detail some examples for audio playback synchronization amongplayback devices.

To facilitate audio playback, the playback device 102 includes audioprocessing components 216 that are generally configured to process audioprior to the playback device 102 rendering the audio. In this respect,the audio processing components 216 may include one or moredigital-to-analog converters (“DAC”), one or more audio preprocessingcomponents, one or more audio enhancement components, one or moredigital signal processors (“DSPs”), and so on. In some implementations,one or more of the audio processing components 216 may be a subcomponentof the processor 212. In operation, the audio processing components 216receive analog and/or digital audio and process and/or otherwiseintentionally alter the audio to produce audio signals for playback.

The produced audio signals may then be provided to one or more audioamplifiers 217 for amplification and playback through one or morespeakers 218 operably coupled to the amplifiers 217. The audioamplifiers 217 may include components configured to amplify audiosignals to a level for driving one or more of the speakers 218.

Each of the speakers 218 may include an individual transducer (e.g., a“driver”) or the speakers 218 may include a complete speaker systeminvolving an enclosure with one or more drivers. A particular driver ofa speaker 218 may include, for example, a subwoofer (e.g., for lowfrequencies), a mid-range driver (e.g., for middle frequencies), and/ora tweeter (e.g., for high frequencies). In some cases, a transducer maybe driven by an individual corresponding audio amplifier of the audioamplifiers 217. In some implementations, a playback device may notinclude the speakers 218, but instead may include a speaker interfacefor connecting the playback device to external speakers. In certainembodiments, a playback device may include neither the speakers 218 northe audio amplifiers 217, but instead may include an audio interface(not shown) for connecting the playback device to an external audioamplifier or audio-visual receiver.

In addition to producing audio signals for playback by the playbackdevice 102, the audio processing components 216 may be configured toprocess audio to be sent to one or more other playback devices, via thenetwork interface 224, for playback. In example scenarios, audio contentto be processed and/or played back by the playback device 102 may bereceived from an external source, such as via an audio line-in interface(e.g., an auto-detecting 3.5 mm audio line-in connection) of theplayback device 102 (not shown) or via the network interface 224, asdescribed below.

As shown, the at least one network interface 224, may take the form ofone or more wireless interfaces 225 and/or one or more wired interfaces226. A wireless interface may provide network interface functions forthe playback device 102 to wirelessly communicate with other devices(e.g., other playback device(s), NMD(s), and/or controller device(s)) inaccordance with a communication protocol (e.g., any wireless standardincluding IEEE 802.11a, 802.11b, 802.11g, 802.11n, 802.11ac, 802.15, 4Gmobile communication standard, and so on). A wired interface may providenetwork interface functions for the playback device 102 to communicateover a wired connection with other devices in accordance with acommunication protocol (e.g., IEEE 802.3). While the network interface224 shown in FIG. 2A include both wired and wireless interfaces, theplayback device 102 may in some implementations include only wirelessinterface(s) or only wired interface(s).

In general, the network interface 224 facilitates data flow between theplayback device 102 and one or more other devices on a data network. Forinstance, the playback device 102 may be configured to receive audiocontent over the data network from one or more other playback devices,network devices within a LAN, and/or audio content sources over a WAN,such as the Internet. In one example, the audio content and othersignals transmitted and received by the playback device 102 may betransmitted in the form of digital packet data comprising an InternetProtocol (IP)-based source address and IP-based destination addresses.In such a case, the network interface 224 may be configured to parse thedigital packet data such that the data destined for the playback device102 is properly received and processed by the playback device 102.

As shown in FIG. 2A, the playback device 102 also includes voiceprocessing components 220 that are operably coupled to one or moremicrophones 222. The microphones 222 are configured to detect sound(i.e., acoustic waves) in the environment of the playback device 102,which is then provided to the voice processing components 220. Morespecifically, each microphone 222 is configured to detect sound andconvert the sound into a digital or analog signal representative of thedetected sound, which can then cause the voice processing component 220to perform various functions based on the detected sound, as describedin greater detail below. In one implementation, the microphones 222 arearranged as an array of microphones (e.g., an array of six microphones).In some implementations, the playback device 102 includes more than sixmicrophones (e.g., eight microphones or twelve microphones) or fewerthan six microphones (e.g., four microphones, two microphones, or asingle microphones).

In operation, the voice-processing components 220 are generallyconfigured to detect and process sound received via the microphones 222,identify potential voice input in the detected sound, and extractdetected-sound data to enable a VAS, such as the VAS 190 (FIG. 1B), toprocess voice input identified in the detected-sound data. The voiceprocessing components 220 may include one or more analog-to-digitalconverters, an acoustic echo canceller (“AEC”), a spatial processor(e.g., one or more multi-channel Wiener filters, one or more otherfilters, and/or one or more beam former components), one or more buffers(e.g., one or more circular buffers), one or more wake-word engines, oneor more voice extractors, and/or one or more speech processingcomponents (e.g., components configured to recognize a voice of aparticular user or a particular set of users associated with ahousehold), among other example voice processing components. In exampleimplementations, the voice processing components 220 may include orotherwise take the form of one or more DSPs or one or more modules of aDSP. In this respect, certain voice processing components 220 may beconfigured with particular parameters (e.g., gain and/or spectralparameters) that may be modified or otherwise tuned to achieveparticular functions. In some implementations, one or more of the voiceprocessing components 220 may be a subcomponent of the processor 212.

As further shown in FIG. 2A, the playback device 102 also includes powercomponents 227. The power components 227 include at least an externalpower source interface 228, which may be coupled to a power source (notshown) via a power cable or the like that physically connects theplayback device 102 to an electrical outlet or some other external powersource. Other power components may include, for example, transformers,converters, and like components configured to format electrical power.

In some implementations, the power components 227 of the playback device102 may additionally include an internal power source 229 (e.g., one ormore batteries) configured to power the playback device 102 without aphysical connection to an external power source. When equipped with theinternal power source 229, the playback device 102 may operateindependent of an external power source. In some such implementations,the external power source interface 228 may be configured to facilitatecharging the internal power source 229. As discussed before, a playbackdevice comprising an internal power source may be referred to herein asa “portable playback device.” On the other hand, a playback device thatoperates using an external power source may be referred to herein as a“stationary playback device,” although such a device may in fact bemoved around a home or other environment.

The playback device 102 further includes a user interface 240 that mayfacilitate user interactions independent of or in conjunction with userinteractions facilitated by one or more of the controller devices 104.In various embodiments, the user interface 240 includes one or morephysical buttons and/or supports graphical interfaces provided on touchsensitive screen(s) and/or surface(s), among other possibilities, for auser to directly provide input. The user interface 240 may furtherinclude one or more of lights (e.g., LEDs) and the speakers to providevisual and/or audio feedback to a user.

As an illustrative example, FIG. 2B shows an example housing 230 of theplayback device 102 that includes a user interface in the form of acontrol area 232 at a top portion 234 of the housing 230. The controlarea 232 includes buttons 236 a-c for controlling audio playback, volumelevel, and other functions. The control area 232 also includes a button236 d for toggling the microphones 222 to either an on state or an offstate.

As further shown in FIG. 2B, the control area 232 is at least partiallysurrounded by apertures formed in the top portion 234 of the housing 230through which the microphones 222 (not visible in FIG. 2B) receive thesound in the environment of the playback device 102. The microphones 222may be arranged in various positions along and/or within the top portion234 or other areas of the housing 230 so as to detect sound from one ormore directions relative to the playback device 102.

By way of illustration, SONOS, Inc. presently offers (or has offered)for sale certain playback devices that may implement certain of theembodiments disclosed herein, including a “PLAY:1,” “PLAY:3,” “PLAY:5,”“PLAYBAR,” “CONNECT:AMP,” “PLAYBASE,” “BEAM,” “CONNECT,” and “SUB.” Anyother past, present, and/or future playback devices may additionally oralternatively be used to implement the playback devices of exampleembodiments disclosed herein. Additionally, it should be understood thata playback device is not limited to the examples illustrated in FIG. 2Aor 2B or to the SONOS product offerings. For example, a playback devicemay include, or otherwise take the form of, a wired or wirelessheadphone set, which may operate as a part of the MPS 100 via a networkinterface or the like. In another example, a playback device may includeor interact with a docking station for personal mobile media playbackdevices. In yet another example, a playback device may be integral toanother device or component such as a television, a lighting fixture, orsome other device for indoor or outdoor use.

FIG. 2C is a diagram of an example voice input 280 that may be processedby an NMD or an NMD-equipped playback device. The voice input 280 mayinclude a keyword portion 280 a and an utterance portion 280 b. Thekeyword portion 280 a may include a wake word or a local keyword.

In the case of a wake word, the keyword portion 280 a corresponds todetected sound that caused a VAS wake-word event. In practice, a wakeword is typically a predetermined nonce word or phrase used to “wake up”an NMD and cause it to invoke a particular voice assistant service(“VAS”) to interpret the intent of voice input in detected sound. Forexample, a user might speak the wake word “Alexa” to invoke the AMAZON®VAS, “Ok, Google” to invoke the GOOGLE® VAS, or “Hey, Siri” to invokethe APPLE® VAS, among other examples. In practice, a wake word may alsobe referred to as, for example, an activation-, trigger-, wakeup-wordor—phrase, and may take the form of any suitable word, combination ofwords (e.g., a particular phrase), and/or some other audio cue.

The utterance portion 280 b corresponds to detected sound thatpotentially comprises a user request following the keyword portion 280a. An utterance portion 280 b can be processed to identify the presenceof any words in detected-sound data by the NMD in response to the eventcaused by the keyword portion 280 a. In various implementations, anunderlying intent can be determined based on the words in the utteranceportion 280 b. In certain implementations, an underlying intent can alsobe based or at least partially based on certain words in the keywordportion 280 a, such as when keyword portion includes a command keyword.In any case, the words may correspond to one or more commands, as wellas a certain command and certain keywords.

A keyword in the voice utterance portion 280 b may be, for example, aword identifying a particular device or group in the MPS 100. Forinstance, in the illustrated example, the keywords in the voiceutterance portion 280 b may be one or more words identifying one or morezones in which the music is to be played, such as the Living Room andthe Dining Room (FIG. 1A). In some cases, the utterance portion 280 bmay include additional information, such as detected pauses (e.g.,periods of non-speech) between words spoken by a user, as shown in FIG.2C. The pauses may demarcate the locations of separate commands,keywords, or other information spoke by the user within the utteranceportion 280 b.

Based on certain command criteria, the NMD and/or a remote VAS may takeactions as a result of identifying one or more commands in the voiceinput. Command criteria may be based on the inclusion of certainkeywords within the voice input, among other possibilities.Additionally, AMAstate and/or zone-state variables in conjunction withidentification of one or more particular commands. Control-statevariables may include, for example, indicators identifying a level ofvolume, a queue associated with one or more devices, and playback state,such as whether devices are playing a queue, paused, etc. Zone-statevariables may include, for example, indicators identifying which, ifany, zone players are grouped.

In some implementations, the MPS 100 is configured to temporarily reducethe volume of audio content that it is playing upon detecting a certainkeyword, such as a wake word, in the keyword portion 280 a. The MPS 100may restore the volume after processing the voice input 280. Such aprocess can be referred to as ducking, examples of which are disclosedin U.S. patent application Ser. No. 15/438,749, incorporated byreference herein in its entirety.

FIG. 2D shows an example sound specimen. In this example, the soundspecimen corresponds to the sound-data stream (e.g., one or more audioframes) associated with a spotted wake word or command keyword in thekeyword portion 280 a of FIG. 2A. As illustrated, the example soundspecimen comprises sound detected in an NMD's environment (i)immediately before a wake or command word was spoken, which may bereferred to as a pre-roll portion (between times t₀ and t₁), (ii) whilea wake or command word was spoken, which may be referred to as awake-meter portion (between times t₁ and t₂), and/or (iii) after thewake or command word was spoken, which may be referred to as a post-rollportion (between times t₂ and t₃). Other sound specimens are alsopossible. In various implementations, aspects of the sound specimen canbe evaluated according to an acoustic model which aims to mapmels/spectral features to phonemes in a given language model for furtherprocessing. For example, automatic speech recognition (ASR) may includesuch mapping for command-keyword detection. Wake-word detection engines,by contrast, may be precisely tuned to identify a specific wake-word,and a downstream action of invoking a VAS (e.g., by targeting only noncewords in the voice input processed by the playback device).

ASR for local keyword detection may be tuned to accommodate a wide rangeof keywords (e.g., 5, 10, 100, 1,000, 10,000 keywords). Local keyworddetection, in contrast to wake-word detection, may involve feeding ASRoutput to an onboard, local NLU which together with the ASR determinewhen local keyword events have occurred. In some implementationsdescribed below, the local NLU may determine an intent based on one ormore keywords in the ASR output produced by a particular voice input. Inthese or other implementations, a playback device may act on a detectedcommand keyword event only when the playback devices determines thatcertain conditions have been met, such as environmental conditions(e.g., low background noise).

b. Example Playback Device Configurations

FIGS. 3A-3E show example configurations of playback devices. Referringfirst to FIG. 3A, in some example instances, a single playback devicemay belong to a zone. For example, the playback device 102 c (FIG. 1A)on the Patio may belong to Zone A. In some implementations describedbelow, multiple playback devices may be “bonded” to form a “bondedpair,” which together form a single zone. For example, the playbackdevice 102 f (FIG. 1A) named “Bed 1” in FIG. 3A may be bonded to theplayback device 102 g (FIG. 1A) named “Bed 2” in FIG. 3A to form Zone B.Bonded playback devices may have different playback responsibilities(e.g., channel responsibilities). In another implementation describedbelow, multiple playback devices may be merged to form a single zone.For example, the playback device 102 d named “Bookcase” may be mergedwith the playback device 102 m named “Living Room” to form a single ZoneC. The merged playback devices 102 d and 102 m may not be specificallyassigned different playback responsibilities. That is, the mergedplayback devices 102 d and 102 m may, aside from playing audio contentin synchrony, each play audio content as they would if they were notmerged.

For purposes of control, each zone in the MPS 100 may be represented asa single user interface (“UP”) entity. For example, as displayed by thecontroller devices 104, Zone A may be provided as a single entity named“Portable,” Zone B may be provided as a single entity named “Stereo,”and Zone C may be provided as a single entity named “Living Room.”

In various embodiments, a zone may take on the name of one of theplayback devices belonging to the zone. For example, Zone C may take onthe name of the Living Room device 102 m (as shown). In another example,Zone C may instead take on the name of the Bookcase device 102 d. In afurther example, Zone C may take on a name that is some combination ofthe Bookcase device 102 d and Living Room device 102 m. The name that ischosen may be selected by a user via inputs at a controller device 104.In some embodiments, a zone may be given a name that is different thanthe device(s) belonging to the zone. For example, Zone B in FIG. 3A isnamed “Stereo” but none of the devices in Zone B have this name. In oneaspect, Zone B is a single UI entity representing a single device named“Stereo,” composed of constituent devices “Bed 1” and “Bed 2.” In oneimplementation, the Bed 1 device may be playback device 102 f in themaster bedroom 101 h (FIG. 1A) and the Bed 2 device may be the playbackdevice 102 g also in the master bedroom 101 h (FIG. 1A).

As noted above, playback devices that are bonded may have differentplayback responsibilities, such as playback responsibilities for certainaudio channels. For example, as shown in FIG. 3B, the Bed 1 and Bed 2devices 102 f and 102 g may be bonded so as to produce or enhance astereo effect of audio content. In this example, the Bed 1 playbackdevice 102 f may be configured to play a left channel audio component,while the Bed 2 playback device 102 g may be configured to play a rightchannel audio component. In some implementations, such stereo bondingmay be referred to as “pairing.”

Additionally, playback devices that are configured to be bonded may haveadditional and/or different respective speaker drivers. As shown in FIG.3C, the playback device 102 b named “Front” may be bonded with theplayback device 102 k named “SUB.” The Front device 102 b may render arange of mid to high frequencies, and the SUB device 102 k may renderlow frequencies as, for example, a subwoofer. When unbonded, the Frontdevice 102 b may be configured to render a full range of frequencies. Asanother example, FIG. 3D shows the Front and SUB devices 102 b and 102 kfurther bonded with Right and Left playback devices 102 a and 102 j,respectively. In some implementations, the Right and Left devices 102 aand 102 j may form surround or “satellite” channels of a home theatersystem. The bonded playback devices 102 a, 102 b, 102 j, and 102 k mayform a single Zone D (FIG. 3A).

In some implementations, playback devices may also be “merged.” Incontrast to certain bonded playback devices, playback devices that aremerged may not have assigned playback responsibilities, but may eachrender the full range of audio content that each respective playbackdevice is capable of Nevertheless, merged devices may be represented asa single UI entity (i.e., a zone, as discussed above). For instance,FIG. 3E shows the playback devices 102 d and 102 m in the Living Roommerged, which would result in these devices being represented by thesingle UI entity of Zone C. In one embodiment, the playback devices 102d and 102 m may playback audio in synchrony, during which each outputsthe full range of audio content that each respective playback device 102d and 102 m is capable of rendering.

In some embodiments, a stand-alone NMD may be in a zone by itself. Forexample, the NMD 103 h from FIG. 1A is named “Closet” and forms Zone Iin FIG. 3A. An NMD may also be bonded or merged with another device soas to form a zone. For example, the NMD device 103 f named “Island” maybe bonded with the playback device 102 i Kitchen, which together formZone F, which is also named “Kitchen.” Additional details regardingassigning NMDs and playback devices as designated or default devices maybe found, for example, in previously referenced U.S. patent applicationSer. No. 15/438,749. In some embodiments, a stand-alone NMD may not beassigned to a zone.

Zones of individual, bonded, and/or merged devices may be arranged toform a set of playback devices that playback audio in synchrony. Such aset of playback devices may be referred to as a “group,” “zone group,”“synchrony group,” or “playback group.” In response to inputs providedvia a controller device 104, playback devices may be dynamically groupedand ungrouped to form new or different groups that synchronously playback audio content. For example, referring to FIG. 3A, Zone A may begrouped with Zone B to form a zone group that includes the playbackdevices of the two zones. As another example, Zone A may be grouped withone or more other Zones C-I. The Zones A-I may be grouped and ungroupedin numerous ways. For example, three, four, five, or more (e.g., all) ofthe Zones A-I may be grouped. When grouped, the zones of individualand/or bonded playback devices may play back audio in synchrony with oneanother, as described in previously referenced U.S. Pat. No. 8,234,395.Grouped and bonded devices are example types of associations betweenportable and stationary playback devices that may be caused in responseto a trigger event, as discussed above and described in greater detailbelow.

In various implementations, the zones in an environment may be assigneda particular name, which may be the default name of a zone within a zonegroup or a combination of the names of the zones within a zone group,such as “Dining Room+Kitchen,” as shown in FIG. 3A. In some embodiments,a zone group may be given a unique name selected by a user, such as“Nick's Room,” as also shown in FIG. 3A. The name “Nick's Room” may be aname chosen by a user over a prior name for the zone group, such as theroom name “Master Bedroom.”

Referring back to FIG. 2A, certain data may be stored in the memory 213as one or more state variables that are periodically updated and used todescribe the state of a playback zone, the playback device(s), and/or azone group associated therewith. The memory 213 may also include thedata associated with the state of the other devices of the MPS 100,which may be shared from time to time among the devices so that one ormore of the devices have the most recent data associated with thesystem.

In some embodiments, the memory 213 of the playback device 102 may storeinstances of various variable types associated with the states.Variables instances may be stored with identifiers (e.g., tags)corresponding to type. For example, certain identifiers may be a firsttype “a1” to identify playback device(s) of a zone, a second type “b1”to identify playback device(s) that may be bonded in the zone, and athird type “cl” to identify a zone group to which the zone may belong.As a related example, in FIG. 1A, identifiers associated with the Patiomay indicate that the Patio is the only playback device of a particularzone and not in a zone group. Identifiers associated with the LivingRoom may indicate that the Living Room is not grouped with other zonesbut includes bonded playback devices 102 a, 102 b, 102 j, and 102 k.Identifiers associated with the Dining Room may indicate that the DiningRoom is part of Dining Room+Kitchen group and that devices 103 f and 102i are bonded. Identifiers associated with the Kitchen may indicate thesame or similar information by virtue of the Kitchen being part of theDining Room+Kitchen zone group. Other example zone variables andidentifiers are described below.

In yet another example, the MPS 100 may include variables or identifiersrepresenting other associations of zones and zone groups, such asidentifiers associated with Areas, as shown in FIG. 3A. An Area mayinvolve a cluster of zone groups and/or zones not within a zone group.For instance, FIG. 3A shows a first area named “First Area” and a secondarea named “Second Area.” The First Area includes zones and zone groupsof the Patio, Den, Dining Room, Kitchen, and Bathroom. The Second Areaincludes zones and zone groups of the Bathroom, Nick's Room, Bedroom,and Living Room. In one aspect, an Area may be used to invoke a clusterof zone groups and/or zones that share one or more zones and/or zonegroups of another cluster. In this respect, such an Area differs from azone group, which does not share a zone with another zone group. Furtherexamples of techniques for implementing Areas may be found, for example,in U.S. application Ser. No. 15/682,506 filed Aug. 21, 2017 and titled“Room Association Based on Name,” and U.S. Pat. No. 8,483,853 filed Sep.11, 2007, and titled “Controlling and manipulating groupings in amulti-zone media system.” Each of these applications is incorporatedherein by reference in its entirety. In some embodiments, the MPS 100may not implement Areas, in which case the system may not storevariables associated with Areas.

The memory 213 may be further configured to store other data. Such datamay pertain to audio sources accessible by the playback device 102 or aplayback queue that the playback device (or some other playbackdevice(s)) may be associated with. In embodiments described below, thememory 213 is configured to store a set of command data for selecting aparticular VAS when processing voice inputs. During operation, one ormore playback zones in the environment of FIG. 1A may each be playingdifferent audio content. For instance, the user may be grilling in thePatio zone and listening to hip hop music being played by the playbackdevice 102 c, while another user may be preparing food in the Kitchenzone and listening to classical music being played by the playbackdevice 102 i. In another example, a playback zone may play the sameaudio content in synchrony with another playback zone.

For instance, the user may be in the Office zone where the playbackdevice 102 n is playing the same hip-hop music that is being playing byplayback device 102 c in the Patio zone. In such a case, playbackdevices 102 c and 102 n may be playing the hip-hop in synchrony suchthat the user may seamlessly (or at least substantially seamlessly)enjoy the audio content that is being played out-loud while movingbetween different playback zones. Synchronization among playback zonesmay be achieved in a manner similar to that of synchronization amongplayback devices, as described in previously referenced U.S. Pat. No.8,234,395.

As suggested above, the zone configurations of the MPS 100 may bedynamically modified. As such, the MPS 100 may support numerousconfigurations. For example, if a user physically moves one or moreplayback devices to or from a zone, the MPS 100 may be reconfigured toaccommodate the change(s). For instance, if the user physically movesthe playback device 102 c from the Patio zone to the Office zone, theOffice zone may now include both the playback devices 102 c and 102 n.In some cases, the user may pair or group the moved playback device 102c with the Office zone and/or rename the players in the Office zoneusing, for example, one of the controller devices 104 and/or voiceinput. As another example, if one or more playback devices 102 are movedto a particular space in the home environment that is not already aplayback zone, the moved playback device(s) may be renamed or associatedwith a playback zone for the particular space.

Further, different playback zones of the MPS 100 may be dynamicallycombined into zone groups or split up into individual playback zones.For example, the Dining Room zone and the Kitchen zone may be combinedinto a zone group for a dinner party such that playback devices 102 iand 102 l may render audio content in synchrony. As another example,bonded playback devices in the Den zone may be split into (i) atelevision zone and (ii) a separate listening zone. The television zonemay include the Front playback device 102 b. The listening zone mayinclude the Right, Left, and SUB playback devices 102 a, 102 j, and 102k, which may be grouped, paired, or merged, as described above.Splitting the Den zone in such a manner may allow one user to listen tomusic in the listening zone in one area of the living room space, andanother user to watch the television in another area of the living roomspace. In a related example, a user may utilize either of the NMD 103 aor 103 b (FIG. 1B) to control the Den zone before it is separated intothe television zone and the listening zone. Once separated, thelistening zone may be controlled, for example, by a user in the vicinityof the NMD 103 a, and the television zone may be controlled, forexample, by a user in the vicinity of the NMD 103 b. As described above,however, any of the NMDs 103 may be configured to control the variousplayback and other devices of the MPS 100.

c. Example Controller Devices

FIG. 4 is a functional block diagram illustrating certain aspects of aselected one of the controller devices 104 of the MPS 100 of FIG. 1A.Such controller devices may also be referred to herein as a “controldevice” or “controller.” The controller device shown in FIG. 4 mayinclude components that are generally similar to certain components ofthe network devices described above, such as a processor 412, memory 413storing program software 414, at least one network interface 424, andone or more microphones 422. In one example, a controller device may bea dedicated controller for the MPS 100. In another example, a controllerdevice may be a network device on which media playback system controllerapplication software may be installed, such as for example, an iPhone™,iPad™ or any other smart phone, tablet, or network device (e.g., anetworked computer such as a PC or Mac™).

The memory 413 of the controller device 104 may be configured to storecontroller application software and other data associated with the MPS100 and/or a user of the system 100. The memory 413 may be loaded withinstructions in software 414 that are executable by the processor 412 toachieve certain functions, such as facilitating user access, control,and/or configuration of the MPS 100. The controller device 104 isconfigured to communicate with other network devices via the networkinterface 424, which may take the form of a wireless interface, asdescribed above.

In one example, system information (e.g., such as a state variable) maybe communicated between the controller device 104 and other devices viathe network interface 424. For instance, the controller device 104 mayreceive playback zone and zone group configurations in the MPS 100 froma playback device, an NMD, or another network device. Likewise, thecontroller device 104 may transmit such system information to a playbackdevice or another network device via the network interface 424. In somecases, the other network device may be another controller device.

The controller device 104 may also communicate playback device controlcommands, such as volume control and audio playback control, to aplayback device via the network interface 424. As suggested above,changes to configurations of the MPS 100 may also be performed by a userusing the controller device 104. The configuration changes may includeadding/removing one or more playback devices to/from a zone,adding/removing one or more zones to/from a zone group, forming a bondedor merged player, separating one or more playback devices from a bondedor merged player, among others.

As shown in FIG. 4, the controller device 104 also includes a userinterface 440 that is generally configured to facilitate user access andcontrol of the MPS 100. The user interface 440 may include atouch-screen display or other physical interface configured to providevarious graphical controller interfaces, such as the controllerinterfaces 540 a and 540 b shown in FIGS. 5A and 5B. Referring to FIGS.5A and 5B together, the controller interfaces 540 a and 540 b includes aplayback control region 542, a playback zone region 543, a playbackstatus region 544, a playback queue region 546, and a sources region548. The user interface as shown is just one example of an interfacethat may be provided on a network device, such as the controller deviceshown in FIG. 4, and accessed by users to control a media playbacksystem, such as the MPS 100. Other user interfaces of varying formats,styles, and interactive sequences may alternatively be implemented onone or more network devices to provide comparable control access to amedia playback system.

The playback control region 542 (FIG. 5A) may include selectable icons(e.g., by way of touch or by using a cursor) that, when selected, causeplayback devices in a selected playback zone or zone group to play orpause, fast forward, rewind, skip to next, skip to previous, enter/exitshuffle mode, enter/exit repeat mode, enter/exit cross fade mode, etc.The playback control region 542 may also include selectable icons that,when selected, modify equalization settings and/or playback volume,among other possibilities.

The playback zone region 543 (FIG. 5B) may include representations ofplayback zones within the MPS 100. The playback zones regions 543 mayalso include a representation of zone groups, such as the DiningRoom+Kitchen zone group, as shown.

In some embodiments, the graphical representations of playback zones maybe selectable to bring up additional selectable icons to manage orconfigure the playback zones in the MPS 100, such as a creation ofbonded zones, creation of zone groups, separation of zone groups, andrenaming of zone groups, among other possibilities.

For example, as shown, a “group” icon may be provided within each of thegraphical representations of playback zones. The “group” icon providedwithin a graphical representation of a particular zone may be selectableto bring up options to select one or more other zones in the MPS 100 tobe grouped with the particular zone. Once grouped, playback devices inthe zones that have been grouped with the particular zone will beconfigured to play audio content in synchrony with the playbackdevice(s) in the particular zone. Analogously, a “group” icon may beprovided within a graphical representation of a zone group. In thiscase, the “group” icon may be selectable to bring up options to deselectone or more zones in the zone group to be removed from the zone group.Other interactions and implementations for grouping and ungrouping zonesvia a user interface are also possible. The representations of playbackzones in the playback zone region 543 (FIG. 5B) may be dynamicallyupdated as playback zone or zone group configurations are modified.

The playback status region 544 (FIG. 5A) may include graphicalrepresentations of audio content that is presently being played,previously played, or scheduled to play next in the selected playbackzone or zone group. The selected playback zone or zone group may bevisually distinguished on a controller interface, such as within theplayback zone region 543 and/or the playback status region 544. Thegraphical representations may include track title, artist name, albumname, album year, track length, and/or other relevant information thatmay be useful for the user to know when controlling the MPS 100 via acontroller interface.

The playback queue region 546 may include graphical representations ofaudio content in a playback queue associated with the selected playbackzone or zone group. In some embodiments, each playback zone or zonegroup may be associated with a playback queue comprising informationcorresponding to zero or more audio items for playback by the playbackzone or zone group. For instance, each audio item in the playback queuemay comprise a uniform resource identifier (URI), a uniform resourcelocator (URL), or some other identifier that may be used by a playbackdevice in the playback zone or zone group to find and/or retrieve theaudio item from a local audio content source or a networked audiocontent source, which may then be played back by the playback device.

In one example, a playlist may be added to a playback queue, in whichcase information corresponding to each audio item in the playlist may beadded to the playback queue. In another example, audio items in aplayback queue may be saved as a playlist. In a further example, aplayback queue may be empty, or populated but “not in use” when theplayback zone or zone group is playing continuously streamed audiocontent, such as Internet radio that may continue to play untilotherwise stopped, rather than discrete audio items that have playbackdurations. In an alternative embodiment, a playback queue can includeInternet radio and/or other streaming audio content items and be “inuse” when the playback zone or zone group is playing those items. Otherexamples are also possible.

When playback zones or zone groups are “grouped” or “ungrouped,”playback queues associated with the affected playback zones or zonegroups may be cleared or re-associated. For example, if a first playbackzone including a first playback queue is grouped with a second playbackzone including a second playback queue, the established zone group mayhave an associated playback queue that is initially empty, that containsaudio items from the first playback queue (such as if the secondplayback zone was added to the first playback zone), that contains audioitems from the second playback queue (such as if the first playback zonewas added to the second playback zone), or a combination of audio itemsfrom both the first and second playback queues. Subsequently, if theestablished zone group is ungrouped, the resulting first playback zonemay be re-associated with the previous first playback queue or may beassociated with a new playback queue that is empty or contains audioitems from the playback queue associated with the established zone groupbefore the established zone group was ungrouped. Similarly, theresulting second playback zone may be re-associated with the previoussecond playback queue or may be associated with a new playback queuethat is empty or contains audio items from the playback queue associatedwith the established zone group before the established zone group wasungrouped. Other examples are also possible.

With reference still to FIGS. 5A and 5B, the graphical representationsof audio content in the playback queue region 646 (FIG. 5A) may includetrack titles, artist names, track lengths, and/or other relevantinformation associated with the audio content in the playback queue. Inone example, graphical representations of audio content may beselectable to bring up additional selectable icons to manage and/ormanipulate the playback queue and/or audio content represented in theplayback queue. For instance, a represented audio content may be removedfrom the playback queue, moved to a different position within theplayback queue, or selected to be played immediately, or after anycurrently playing audio content, among other possibilities. A playbackqueue associated with a playback zone or zone group may be stored in amemory on one or more playback devices in the playback zone or zonegroup, on a playback device that is not in the playback zone or zonegroup, and/or some other designated device. Playback of such a playbackqueue may involve one or more playback devices playing back media itemsof the queue, perhaps in sequential or random order.

The sources region 548 may include graphical representations ofselectable audio content sources and/or selectable voice assistantsassociated with a corresponding VAS. The VASes may be selectivelyassigned. In some examples, multiple VASes, such as AMAZON's Alexa,MICROSOFT's Cortana, etc., may be invokable by the same NMD. In someembodiments, a user may assign a VAS exclusively to one or more NMDs.For example, a user may assign a first VAS to one or both of the NMDs102 a and 102 b in the Living Room shown in FIG. 1A, and a second VAS tothe NMD 103 f in the Kitchen. Other examples are possible.

d. Example Audio Content Sources

The audio sources in the sources region 548 may be audio content sourcesfrom which audio content may be retrieved and played by the selectedplayback zone or zone group. One or more playback devices in a zone orzone group may be configured to retrieve for playback audio content(e.g., according to a corresponding URI or URL for the audio content)from a variety of available audio content sources. In one example, audiocontent may be retrieved by a playback device directly from acorresponding audio content source (e.g., via a line-in connection). Inanother example, audio content may be provided to a playback device overa network via one or more other playback devices or network devices. Asdescribed in greater detail below, in some embodiments audio content maybe provided by one or more media content services.

Example audio content sources may include a memory of one or moreplayback devices in a media playback system such as the MPS 100 of FIG.1, local music libraries on one or more network devices (e.g., acontroller device, a network-enabled personal computer, or anetworked-attached storage (“NAS”)), streaming audio services providingaudio content via the Internet (e.g., cloud-based music services), oraudio sources connected to the media playback system via a line-in inputconnection on a playback device or network device, among otherpossibilities.

In some embodiments, audio content sources may be added or removed froma media playback system such as the MPS 100 of FIG. 1A. In one example,an indexing of audio items may be performed whenever one or more audiocontent sources are added, removed, or updated. Indexing of audio itemsmay involve scanning for identifiable audio items in allfolders/directories shared over a network accessible by playback devicesin the media playback system and generating or updating an audio contentdatabase comprising metadata (e.g., title, artist, album, track length,among others) and other associated information, such as a URI or URL foreach identifiable audio item found. Other examples for managing andmaintaining audio content sources may also be possible.

FIG. 6 is a message flow diagram illustrating data exchanges betweendevices of the MPS 100. At step 650 a, the MPS 100 receives anindication of selected media content (e.g., one or more songs, albums,playlists, podcasts, videos, stations) via the control device 104. Theselected media content can comprise, for example, media items storedlocally on or more devices (e.g., the audio source 105 of FIG. 1C)connected to the media playback system and/or media items stored on oneor more media service servers (one or more of the remote computingdevices 106 of FIG. 1B). In response to receiving the indication of theselected media content, the control device 104 transmits a message 651 ato the playback device 102 (FIGS. 1A-1C) to add the selected mediacontent to a playback queue on the playback device 102.

At step 650 b, the playback device 102 receives the message 651 a andadds the selected media content to the playback queue for play back.

At step 650 c, the control device 104 receives input corresponding to acommand to play back the selected media content. In response toreceiving the input corresponding to the command to play back theselected media content, the control device 104 transmits a message 651 bto the playback device 102 causing the playback device 102 to play backthe selected media content. In response to receiving the message 651 b,the playback device 102 transmits a message 651 c to the computingdevice 106 requesting the selected media content. The computing device106, in response to receiving the message 651 c, transmits a message 651d comprising data (e.g., audio data, video data, a URL, a URI)corresponding to the requested media content.

At step 650 d, the playback device 102 receives the message 651 d withthe data corresponding to the requested media content and plays back theassociated media content.

At step 650 e, the playback device 102 optionally causes one or moreother devices to play back the selected media content. In one example,the playback device 102 is one of a bonded zone of two or more players(FIG. 1M). The playback device 102 can receive the selected mediacontent and transmit all or a portion of the media content to otherdevices in the bonded zone. In another example, the playback device 102is a coordinator of a group and is configured to transmit and receivetiming information from one or more other devices in the group. Theother one or more devices in the group can receive the selected mediacontent from the computing device 106, and begin playback of theselected media content in response to a message from the playback device102 such that all of the devices in the group play back the selectedmedia content in synchrony.

III. Example Network Microphone Device

FIG. 7A is a functional block diagram illustrating certain aspects of anexample network microphone device (NMD) 703. Generally, the NMD 703 maybe similar to the network microphone device(s) 103 illustrated in FIGS.1A and 1B. As shown, the NMD 703 includes various components, each ofwhich is discussed in further detail below. The various components ofthe NMD 703 may be operably coupled to one another via a system bus,communication network, or some other connection mechanism.

Many of these components are similar to the playback device 102 of FIG.2A. In some examples, the NMD 703 may be implemented in a playbackdevice 102. In such cases, the NMD 703 might not include duplicatecomponents (e.g., a network interface 224 and a network 724), but mayinstead share several components to carry out both playback and voicecontrol functions. Alternatively, within some examples, the NMD 703 isnot designed for audio content playback and therefore may exclude audioprocessing components 216, amplifiers 217, and/or speakers 218 or mayinclude relatively less capable versions of these components (e.g., lesspowerful amplifier(s) 217 and/or smaller speakers 218)).

As shown, the NMD 703 includes at least one processor 712, which may bea clock-driven computing component configured to process input dataaccording to instructions stored in memory 713. The memory 713 may be atangible, non-transitory, computer-readable medium configured to storeinstructions that are executable by the processor 712. For example, thememory 713 may be data storage that can be loaded with software code 714that is executable by the processor 712 to achieve certain functions.

The at least one network interface 724 may take the form of one or morewireless interfaces 725 and/or one or more wired interfaces 726. Thewireless interface 725 may provide network interface functions for theNMD 703 to wirelessly communicate with other devices (e.g., playbackdevice(s) 102, other NMD(s) 103, and/or controller device(s) 104) inaccordance with a communication protocol (e.g., any wireless standardincluding IEEE 802.11a, 802.11b, 802.11g, 802.11n, 802.11ac, 802.15, 4Gmobile communication standard, and so on). The wired interface 726 mayprovide network interface functions for the NMD 703 to communicate overa wired connection with other devices in accordance with a communicationprotocol (e.g., IEEE 802.3). While the network interface 724 shown inFIG. 7A includes both wired and wireless interfaces, the playback device102 may in various implementations include only wireless interface(s) oronly wired interface(s).

As shown in FIG. 7A, the NMD 703 also includes voice processingcomponents 720 that are operably coupled to microphones 722. Themicrophones 722 are configured to detect sound (i.e., acoustic waves) inthe environment of the NMD 703, which is then provided to the voiceprocessing components 720. More specifically, the microphones 722 areconfigured to detect sound and convert the sound into a digital oranalog signal representative of the detected sound, which can then causethe voice processing component 720 to perform various functions based onthe detected sound, as described in greater detail below. In oneimplementation, the microphones 722 are arranged as one or more arraysof microphones (e.g., an array of six microphones). In someimplementations, the NMD 703 includes more than six microphones (e.g.,eight microphones or twelve microphones) or fewer than six microphones(e.g., four microphones, two microphones, or a single microphone).

In operation, similar to the voice-processing components 220 of theNMD-equipped playback device 102 the voice-processing components 720 aregenerally configured to detect and process sound received via themicrophones 722, identify potential voice input in the detected sound,and extract detected-sound data to enable processing of the voice inputby a cloud-based VAS, such as the VAS 190 (FIG. 1B), or a local NLU. Thevoice processing components 720 may include one or moreanalog-to-digital converters, an acoustic echo canceller (“AEC”), aspatial processor, one or more buffers (e.g., one or more circularbuffers), one or more wake-word engines, one or more voice extractors,and/or one or more speech processing components (e.g., componentsconfigured to recognize a voice of a particular user or a particular setof users associated with a household), among other example voiceprocessing components. In example implementations, the voice processingcomponents 720 may include or otherwise take the form of one or moreDSPs or one or more modules of a DSP. In some implementations, one ormore of the voice processing components 720 may be a subcomponent of theprocessor 712.

As further shown in FIG. 7A, the NMD 703 also includes power components727. The power components 727 include at least an external power sourceinterface 728, which may be coupled to a power source (not shown) via apower cable or the like that physically connects the NMD 703 to anelectrical outlet or some other external power source. Other powercomponents may include, for example, transformers, converters, and likecomponents configured to format electrical power.

In some implementations, the power components 727 of the NMD 703 mayadditionally include an internal power source 729 (e.g., one or morebatteries) configured to power the NMD 703 without a physical connectionto an external power source. When equipped with the internal powersource 729, the NMD 703 may operate independent of an external powersource. In some such implementations, the external power sourceinterface 728 may be configured to facilitate charging the internalpower source 729. As discussed before, a NMD comprising an internalpower source may be referred to herein as a “portable NMD.” On the otherhand, a NMD that operates using an external power source may be referredto herein as a “stationary NMD,” although such a device may in fact bemoved around a home or other environment (e.g., to be connected todifferent power outlets of a home or other building).

The NMD 703 further includes a user interface 740 that may facilitateuser interactions independent of or in conjunction with userinteractions facilitated by one or more of the controller devices 104.In various embodiments, the user interface 740 includes one or morephysical buttons and/or supports graphical interfaces provided on touchsensitive screen(s) and/or surface(s), among other possibilities, for auser to directly provide input. The user interface 740 may furtherinclude one or more of lights (e.g., LEDs) and the speakers to providevisual and/or audio feedback to a user.

As an illustrative example, FIG. 7B shows an isometric view of the NMD703. As shown in FIG. 7B, the NMD 703 includes a housing 730. Thehousing 730 may carry one or more components shown in FIG. 7A. Thehousing 730 includes a user interface 740 a carried on the top portion734 of the housing 730. The user interface 740 includes buttons 736a-736 c for controlling audio playback, volume level, and otherfunctions. The user interface 740 a also includes a button 736 d fortoggling the microphones 722 to either an on state or an off state.

As further shown in FIG. 7B, apertures are formed in the top portion 734of the housing 730 through which the microphones 722 receive sound inthe environment of the NMD 703. The microphones 722 may be arranged invarious positions along and/or within the top portion 734 or other areasof the housing 730 so as to detect sound from one or more directionsrelative to the NMD 703.

FIG. 7C is a functional block diagram showing aspects of an NMD 703configured in accordance with embodiments of the disclosure. Asdescribed in more detail below, the NMD 703 is configured to handlecertain voice inputs locally, without necessarily transmitting datarepresenting the voice input to a VAS. The NMD 703 is also configured toprocess other voice inputs using a voice assistant service.

Referring to the FIG. 7C, the NMD 703 includes voice capture components(“VCC”) 760, a VAS wake-word engine 770 a, and a voice extractor 773.The VAS wake-word engine 770 a and the voice extractor 773 are operablycoupled to the VCC 760. The NMD 703 a further a local wake-word engine771 operably coupled to the VCC 760.

The NMD 703 further includes microphones 722. The microphones 722 of theNMD 703 are configured to provide detected sound, S_(D), from theenvironment of the NMD 703 to the VCC 760. The detected sound S_(D) maytake the form of one or more analog or digital signals. In exampleimplementations, the detected sound S_(D) may be composed of a pluralitysignals associated with respective channels 762 that are fed to the VCC760.

Each channel 762 may correspond to a particular microphone 722. Forexample, an NMD having six microphones may have six correspondingchannels. Each channel of the detected sound S_(D) may bear certainsimilarities to the other channels but may differ in certain regards,which may be due to the position of the given channel's correspondingmicrophone relative to the microphones of other channels. For example,one or more of the channels of the detected sound S_(D) may have agreater signal to noise ratio (“SNR”) of speech to background noise thanother channels.

As further shown in FIG. 7C, the VCC 760 includes an AEC 763, a spatialprocessor 764, and one or more buffers 768. In operation, the AEC 763receives the detected sound S_(D) and filters or otherwise processes thesound to suppress echoes and/or to otherwise improve the quality of thedetected sound S_(D). That processed sound may then be passed to thespatial processor 764.

The spatial processor 764 is typically configured to analyze thedetected sound S_(D) and identify certain characteristics, such as asound's amplitude (e.g., decibel level), frequency spectrum,directionality, etc. In one respect, the spatial processor 764 may helpfilter or suppress ambient noise in the detected sound S_(D) frompotential user speech based on similarities and differences in theconstituent channels 762 of the detected sound S_(D), as discussedabove. As one possibility, the spatial processor 764 may monitor metricsthat distinguish speech from other sounds. Such metrics can include, forexample, energy within the speech band relative to background noise andentropy within the speech band—a measure of spectral structure—which istypically lower in speech than in most common background noise. In someimplementations, the spatial processor 764 may be configured todetermine a speech presence probability, examples of such functionalityare disclosed in U.S. patent application Ser. No. 15/984,073, filed May18, 2018, titled “Linear Filtering for Noise-Suppressed SpeechDetection,” which is incorporated herein by reference in its entirety.

In operation, the one or more buffers 768—one or more of which may bepart of or separate from the memory 713 (FIG. 7A)—capture datacorresponding to the detected sound S_(D). More specifically, the one ormore buffers 768 capture detected-sound data that was processed by theupstream AEC 764 and spatial processor 766.

The network interface 724 may then provide this information to a remoteserver that may be associated with the MPS 100. In one aspect, theinformation stored in the additional buffer 769 does not reveal thecontent of any speech but instead is indicative of certain uniquefeatures of the detected sound itself. In a related aspect, theinformation may be communicated between computing devices, such as thevarious computing devices of the MPS 100, without necessarilyimplicating privacy concerns. In practice, the MPS 100 can use thisinformation to adapt and fine-tune voice processing algorithms,including sensitivity tuning as discussed below. In some implementationsthe additional buffer may comprise or include functionality similar tolookback buffers disclosed, for example, in U.S. patent application Ser.No. 15/989,715, filed May 25, 2018, titled “Determining and Adapting toChanges in Microphone Performance of Playback Devices”; U.S. patentapplication Ser. No. 16/141,875, filed Sep. 25, 2018, titled “VoiceDetection Optimization Based on Selected Voice Assistant Service”; andU.S. patent application Ser. No. 16/138,111, filed Sep. 21, 2018, titled“Voice Detection Optimization Using Sound Metadata,” which areincorporated herein by reference in their entireties.

In any event, the detected-sound data forms a digital representation(i.e., sound-data stream), S_(DS), of the sound detected by themicrophones 720. In practice, the sound-data stream S_(DS) may take avariety of forms. As one possibility, the sound-data stream S_(DS) maybe composed of frames, each of which may include one or more soundsamples. The frames may be streamed (i.e., read out) from the one ormore buffers 768 for further processing by downstream components, suchas the VAS wake-word engines 770 and the voice extractor 773 of the NMD703.

In some implementations, at least one buffer 768 captures detected-sounddata utilizing a sliding window approach in which a given amount (i.e.,a given window) of the most recently captured detected-sound data isretained in the at least one buffer 768 while older detected-sound datais overwritten when it falls outside of the window. For example, atleast one buffer 768 may temporarily retain 20 frames of a soundspecimen at given time, discard the oldest frame after an expirationtime, and then capture a new frame, which is added to the 19 priorframes of the sound specimen.

In practice, when the sound-data stream S_(DS) is composed of frames,the frames may take a variety of forms having a variety ofcharacteristics. As one possibility, the frames may take the form ofaudio frames that have a certain resolution (e.g., 16 bits ofresolution), which may be based on a sampling rate (e.g., 44,100 Hz).Additionally, or alternatively, the frames may include informationcorresponding to a given sound specimen that the frames define, such asmetadata that indicates frequency response, power input level, SNR,microphone channel identification, and/or other information of the givensound specimen, among other examples. Thus, in some embodiments, a framemay include a portion of sound (e.g., one or more samples of a givensound specimen) and metadata regarding the portion of sound. In otherembodiments, a frame may only include a portion of sound (e.g., one ormore samples of a given sound specimen) or metadata regarding a portionof sound.

In any case, downstream components of the NMD 703 may process thesound-data stream S_(DS). For instance, the VAS wake-word engines 770are configured to apply one or more identification algorithms to thesound-data stream S_(DS) (e.g., streamed sound frames) to spot potentialwake words in the detected-sound S_(D). This process may be referred toas automatic speech recognition. The VAS wake-word engine 770 a andlocal wake-word engine 771 apply different identification algorithmscorresponding to their respective wake words, and further generatedifferent events based on detecting a wake word in the detected-soundS_(D).

Example wake word detection algorithms accept audio as input and providean indication of whether a wake word is present in the audio. Manyfirst- and third-party wake word detection algorithms are known andcommercially available. For instance, operators of a voice service maymake their algorithm available for use in third-party devices.Alternatively, an algorithm may be trained to detect certain wake-words.

For instance, when the VAS wake-word engine 770 a detects a potentialVAS wake word, the VAS work-word engine 770 a provides an indication ofa “VAS wake-word event” (also referred to as a “VAS wake-word trigger”).In the illustrated example of FIG. 7A, the VAS wake-word engine 770 aoutputs a signal S_(VW) that indicates the occurrence of a VAS wake-wordevent to the voice extractor 773.

In multi-VAS implementations, the NMD 703 may include a VAS selector 774(shown in dashed lines) that is generally configured to directextraction by the voice extractor 773 and transmission of the sound-datastream S_(DS) to the appropriate VAS when a given wake-word isidentified by a particular wake-word engine (and a correspondingwake-word trigger), such as the VAS wake-word engine 770 a and at leastone additional VAS wake-word engine 770 b (shown in dashed lines). Insuch implementations, the NMD 703 may include multiple, different VASwake-word engines and/or voice extractors, each supported by arespective VAS.

Similar to the discussion above, each VAS wake-word engine 770 may beconfigured to receive as input the sound-data stream S_(DS) from the oneor more buffers 768 and apply identification algorithms to cause awake-word trigger for the appropriate VAS. Thus, as one example, the VASwake-word engine 770 a may be configured to identify the wake word“Alexa” and cause the NMD 703 a to invoke the AMAZON VAS when “Alexa” isspotted. As another example, the wake-word engine 770 b may beconfigured to identify the wake word “Ok, Google” and cause the NMD 520to invoke the GOOGLE VAS when “Ok, Google” is spotted. In single-VASimplementations, the VAS selector 774 may be omitted.

In response to the VAS wake-word event (e.g., in response to the signalS_(VW) indicating the wake-word event), the voice extractor 773 isconfigured to receive and format (e.g., packetize) the sound-data streamS_(DS). For instance, the voice extractor 773 packetizes the frames ofthe sound-data stream S_(DS) into messages. The voice extractor 773transmits or streams these messages, M_(V), that may contain voice inputin real time or near real time to a remote VAS via the network interface724.

In some implementations, a user may selectively enable or disable voiceinput processing via cloud-based voice assistant services. In someexamples, to disable the voice input processing via cloud-based voiceassistant services, the NMD 703 physically or logically disables the VASwake-word engine(s) 770. For instance, the NMD 703 may physically orlogically prevent the sound-data stream S_(DS) from the microphones 722from reaching the VAS wake-word engine(s) 770 and/or voice extractor773. Suppressing generation may involve gating, blocking or otherwisepreventing output from the VAS wake-word engine(s) 770 from generating aVAS wake-word event.

As described in connection with FIG. 2C, the voice input 780 may includea keyword portion and an utterance portion. The keyword portion maycorrespond to detected sound that causes a VAS wake-word event (i.e., aVAS wake word). Alternatively, the keyword portion may correspond to alocal wake word or a command keyword, which may generate a localwake-word event.

For instance, when the voice input 780 includes a VAS wake word, thekeyword portion corresponds to detected sound that causes the wake-wordengine 770 a to output the wake-word event signal S_(VW) to the voiceextractor 773. The utterance portion in this case corresponds todetected sound that potentially comprises a user request following thekeyword portion.

When a VAS wake-word event occurs, the VAS may first process the keywordportion within the sound-data stream S_(DS) to verify the presence of aVAS wake word. In some instances, the VAS may determine that the keywordportion comprises a false wake word (e.g., the word “Election” when theword “Alexa” is the target VAS wake word). In such an occurrence, theVAS may send a response to the NMD 703 with an instruction for the NMD703 to cease extraction of sound data, which causes the voice extractor773 to cease further streaming of the detected-sound data to the VAS.The VAS wake-word engine 770 a may resume or continue monitoring soundspecimens until it spots another potential VAS wake word, leading toanother VAS wake-word event. In some implementations, the VAS does notprocess or receive the keyword portion but instead processes only theutterance portion.

In any case, the VAS processes the utterance portion to identify thepresence of any words in the detected-sound data and to determine anunderlying intent from these words. The words may correspond to one ormore commands, as well as certain keywords. The keyword may be, forexample, a word in the voice input identifying a particular device orgroup in the MPS 100. For instance, in the illustrated example, thekeyword may be one or more words identifying one or more zones in whichthe music is to be played, such as the Living Room and the Dining Room(FIG. 1A).

To determine the intent of the words, the VAS is typically incommunication with one or more databases associated with the VAS (notshown) and/or one or more databases (not shown) of the MPS 100. Suchdatabases may store various user data, analytics, catalogs, and otherinformation for natural language processing and/or other processing. Insome implementations, such databases may be updated for adaptivelearning and feedback for a neural network based on voice-inputprocessing. In some cases, the utterance portion may include additionalinformation such as detected pauses (e.g., periods of non-speech)between words spoken by a user, as shown in FIG. 2C. The pauses maydemarcate the locations of separate commands, keywords, or otherinformation spoke by the user within the utterance portion.

After processing the voice input, the VAS may send a response to the MPS100 with an instruction to perform one or more actions based on anintent it determined from the voice input. For example, based on thevoice input, the VAS may direct the MPS 100 to initiate playback on oneor more of the playback devices 102, control one or more of theseplayback devices 102 (e.g., raise/lower volume, group/ungroup devices,etc.), or turn on/off certain smart devices, among other actions. Afterreceiving the response from the VAS, the wake-word engine 770 a of theNMD 703 may resume or continue to monitor the sound-data stream S_(DS1)until it spots another potential wake-word, as discussed above.

In general, the one or more identification algorithms that a particularVAS wake-word engine, such as the VAS wake-word engine 770 a, appliesare configured to analyze certain characteristics of the detected soundstream S_(DS) and compare those characteristics to correspondingcharacteristics of the particular VAS wake-word engine's one or moreparticular VAS wake words. For example, the wake-word engine 770 a mayapply one or more identification algorithms to spot spectralcharacteristics in the detected sound stream S_(DS) that match thespectral characteristics of the engine's one or more wake words, andthereby determine that the detected sound S_(D) comprises a voice inputincluding a particular VAS wake word.

In some implementations, the one or more identification algorithms maybe third-party identification algorithms (i.e., developed by a companyother than the company that provides the NMD 703 a). For instance,operators of a voice service (e.g., AMAZON) may make their respectivealgorithms (e.g., identification algorithms corresponding to AMAZON'sALEXA) available for use in third-party devices (e.g., the NMDs 103),which are then trained to identify one or more wake words for theparticular voice assistant service. Additionally, or alternatively, theone or more identification algorithms may be first-party identificationalgorithms that are developed and trained to identify certain wake wordsthat are not necessarily particular to a given voice service. Otherpossibilities also exist.

As noted above, the NMD 703 a also includes a local wake-word engine 771in parallel with the VAS wake-word engine 770 a. Like the VAS wake-wordengine 770 a, the local wake-word engine 771 may apply one or moreidentification algorithms corresponding to one or more wake words. A“local wake-word event” is generated when a particular local wake-wordis identified in the detected-sound S_(D). Local wake-words may take theform of a nonce wake word corresponding to local processing (e.g., “HeySonos”), which is different from the VAS wake words corresponding torespective voice assistant services. Exemplary local wake-word detectionis described in “Efficient keyword spotting using dilated convolutionsand gating,” by Alice Coucke et al., published on Nov. 18, 2018,available at https://arxiv.org/pdf/1805.10190.pdf, which is incorporatedby reference herein in its entirety.

Local keywords may also take the form of command keywords. In contrastto the nonce words typically as utilized as VAS wake words, commandkeywords function as both the activation word and the command itself.For instance, example command keywords may correspond to playbackcommands (e.g., “play,” “pause,” “skip,” etc.) as well as controlcommands (“turn on”), among other examples. Under appropriateconditions, based on detecting one of these command keywords, the NMD703 a performs the corresponding command. Examples command keywordeventing is described in U.S. patent application Ser. No. 16/439,009,filed Jun. 12, 2019, titled “Network Microphone Device with CommandKeyword Conditioning,” and available athttps://arxiv.org/pdf/1811.07684v2.pdf, which is incorporated byreference in its entirety.

When a local wake-word event is generated, the NMD 703 can employ anautomatic speech recognizer 775. The ASR 775 is configured to outputphonetic or phenomic representations, such as text corresponding towords, based on sound in the sound-data stream S_(DS) to text. Forinstance, the ASR 775 may transcribe spoken words represented in thesound-data stream S_(DS) to one or more strings representing the voiceinput 780 as text. The ASR 775 can feed ASR output (labeled as S_(ASR))to a local natural language unit (NLU) 776 that identifies particularkeywords as being local keywords for invoking local-keyword events, asdescribed below. Exemplary automatic speech recognition is described in“Snips Voice Platform: an embedded Spoken Language Understanding systemfor private-by-design voice interfaces,” by Alice Coucke et al.,published on May 25, 2018, and available athttps://arxiv.org/pdf/1805.10190.pdf, which is incorporated by referenceherein in its entirety.

As noted above, in some example implementations, the NMD 703 isconfigured to perform natural language processing, which may be carriedout using an onboard natural language processor, referred to herein as anatural language unit (NLU) 776. The local NLU 776 is configured toanalyze text output of the ASR 775 to spot (i.e., detect or identify)keywords in the voice input 780. In FIG. 7A, this output is illustratedas the signal S_(ASR). The local NLU 776 includes a keyword library 778(i.e., words and phrases) corresponding to respective commands and/orparameters.

In one aspect, the library 778 of the local NLU 776 includes localkeywords, which, as noted above, may take the form of commands andparameters. The local NLU 776 may determine an underlying intent fromthe matched keywords in the voice input 780. For instance, if the localNLU matches the keywords “David Bowie” and “kitchen” in combination witha play command, the local NLU 776 may determine an intent of playingDavid Bowie in the Kitchen 101 h on the playback device 102 i. Incontrast to a processing of the voice input 780 by a cloud-based VAS,local processing of the voice input 780 by the local NLU 776 may berelatively less sophisticated, as the NLU 776 does not have access tothe relatively greater processing capabilities and larger voicedatabases that a VAS generally has access to.

In some examples, the local NLU 776 may determine an intent with one ormore slots, which correspond to respective keywords. For instance,referring back to the play David Bowie in the Kitchen example, whenprocessing the voice input, the local NLU 776 may determine that anintent is to play music (e.g., intent=playMusic), while a first slotincludes David Bowie as target content (e.g., slot1=DavidBowie) and asecond slot includes the Kitchen 101 h as the target playback device(e.g., slot2=kitchen). Here, the intent (to “playMusic”) is based on thecommand keyword and the slots are parameters modifying the intent to aparticular target content and playback device.

Within examples, the wake-word engine 771, the ASR 775, and/or the NLU776, referred to together as a local voice input pipeline 777 or,alternatively, a local keyword engine, may operate in one of a firstmode and a second mode, which are referred to herein as a set-up modeand an operating mode, respectively. Initially (e.g., in when firstpowered-on or in a factory reset state), the local voice input pipeline777 may operate in the set-up mode. In the set-up mode, the local NLU776 may enable a portion of the keywords in the local natural languageunit library 778 which may be provided as inputs during set-up. Theset-up mode facilities voice-based set-up of the NMD 703, which mayinclude set-up of one or more VAS(s).

After set-up, the local voice input pipeline 777 may transition tooperating in the operating mode. In some examples, the local voice inputpipeline 777 transitions to the operating mode automatically (e.g.,after set-up is complete). Alternatively, the local voice input pipeline777 transitions to the operating mode when local voice input processingis enabled. Yet further, in some instances, such as if the user 123 optsnot to enable local voice input processing, the local voice inputpipeline 777 may remain in the set-up mode, which allows the local voiceinput pipeline 777 to assist in troubleshooting or further set-up.

As noted above, the local voice input pipeline 777 may transition to theoperating mode when local voice input processing is enabled. Enablinglocal voice input processing may be referred to herein as “adopting” thelocal voice input pipeline 777. In the operating mode, the local NLU 776may enable additional keywords, such as those related to device control.Further, as discussed in more detail below, the local NLU 776 may enablecustom keywords related to the user 123, such as device names,playlists, and other keywords that are unique to the media playbacksystem 100.

Some error in performing local automatic speech recognition is expected.Within examples, the ASR 775 may generate a confidence score whentranscribing spoken words to text, which indicates how closely thespoken words in the voice input 780 matches the sound patterns for thatword. In some implementations, generating a local keyword event is basedon the confidence score for a given local keyword. For instance, thelocal wake word engine 771 may generate a local wake word event when theconfidence score for a given sound exceeds a given threshold value(e.g., 0.5 on a scale of 0-1, indicating that the given sound is morelikely than not a local wake word). Conversely, when the confidencescore for a given sound is at or below the given threshold value, thelocal wake-word engine 771 does not generate the local wake word event.

Similarly, some error in performing keyword matching is expected. Withinexamples, the local NLU 776 may generate a confidence score whendetermining an intent, which indicates how closely the transcribed wordsin the signal S_(ASR) match the corresponding keywords in the library778 of the local NLU 776. In some implementations, performing anoperation according to a determined intent is based on the confidencescore for keywords matched in the signal S_(ASR). For instance, the NMD703 may perform an operation according to a determined intent when theconfidence score for a given sound exceeds a given threshold value(e.g., 0.5 on a scale of 0-1, indicating that the given sound is morelikely than not the command keyword). Conversely, when the confidencescore for a given intent is at or below the given threshold value, theNMD 703 does not perform the operation according to the determinedintent.

As noted above, in some implementations, a phrase may be used as a localkeyword, which provides additional syllables to match (or not match).For instance, the phrase “Hey, Sonos” has more syllables than “Sonos,”which provides additional sound patterns to match to words. As anotherexample, the phrase “play me some music” has more syllables than “play,”which provides additional sound patterns to match to words. Accordingly,local keywords that are phrases may generally be less prone to falsewake words.

In example implementations, the NMD 703 generates a local wake-wordevent based on both a command keyword being detected only when certainconditions corresponding to a detected command keyword are met. Theseconditions are intended to lower the prevalence of false positivecommand keyword events. For instance, after detecting the commandkeyword “skip,” the NMD 703 generates a command keyword event (and skipsto the next track) only when certain playback conditions indicating thata skip should be performed are met. These playback conditions mayinclude, for example, (i) a first condition that a media item is beingplayed back, (ii) a second condition that a queue is active, and (iii) athird condition that the queue includes a media item subsequent to themedia item being played back. If any of these conditions are notsatisfied, the command keyword event is not generated (and no skip isperformed).

The NMD 703 may include one or more state machine(s) 779 to facilitatedetermining whether the appropriate conditions are met. An example statemachine 779 a transitions between a first state and a second state basedon whether one or more conditions corresponding to the detected commandkeyword are met. In particular, for a given command keywordcorresponding to a particular command requiring one or more particularconditions, the state machine 779 a transitions into a first state whenone or more particular conditions are satisfied and transitions into asecond state when at least one condition of the one or more particularconditions is not satisfied.

Within example implementations, the command conditions are based onstates indicated in state variables. As noted above, the devices of theMPS 100 may store state variables describing the state of the respectivedevice. For instance, the playback devices 102 may store state variablesindicating the state of the playback devices 102, such as the audiocontent currently playing (or paused), the volume levels, networkconnection status, and the like). These state variables are updated(e.g., periodically, or based on an event (i.e., when a state in a statevariable changes)) and the state variables further can be shared amongthe devices of the MPS 100, including the NMD 703.

Similarly, the NMD 703 may maintain these state variables (either byvirtue of being implemented in a playback device or as a stand-aloneNMD). The state machine(s) 779 monitor the states indicated in thesestate variables, and determines whether the states indicated in theappropriate state variables indicate that the command condition(s) aresatisfied. Based on these determinations, the state machines 779transition between the first state and the second state, as describedabove.

In some implementations, the local wake word engine 771 is disabledunless certain conditions have been met via the state machines 779. Forexample, the first state and the second state of the state machine 779 amay operate as enable/disable toggles to the local wake word engine 771.In particular, while a state machine 779 a corresponding to a particularcommand keyword is in the first state, the state machine 779 a enablesthe local wake word engine 771 for the particular command keyword.Conversely, while the state machine 779 a corresponding to theparticular command keyword is in the second state, the state machine 779a disables the local wake-word engine 771 for the particular commandkeyword. Accordingly, the disabled local voice input pipeline 777 ceasesanalyzing the sound-data stream S_(DS).

Other example conditions may be based on the output of a voice activitydetector (“VAD”) 765. The VAD 765 is configured to detect the presence(or lack thereof) of voice activity in the sound-data stream S_(DS). Inparticular, the VAD 765 may analyze frames corresponding to the pre-rollportion of the voice input 780 (FIG. 2D) with one or more voicedetection algorithms to determine whether voice activity was present inthe environment in certain time windows prior to a keyword portion ofthe voice input 780.

The VAD 765 may utilize any suitable voice activity detectionalgorithms. Example voice detection algorithms involve determiningwhether a given frame includes one or more features or qualities thatcorrespond to voice activity, and further determining whether thosefeatures or qualities diverge from noise to a given extent (e.g., if avalue exceeds a threshold for a given frame). Some example voicedetection algorithms involve filtering or otherwise reducing noise inthe frames prior to identifying the features or qualities.

In some examples, the VAD 765 may determine whether voice activity ispresent in the environment based on one or more metrics. For example,the VAD 765 can be configured distinguish between frames that includevoice activity and frames that don't include voice activity. The framesthat the VAD determines have voice activity may be caused by speechregardless of whether it near- or far-field. In this example and others,the VAD 765 may determine a count of frames in the pre-roll portion ofthe voice input 780 that indicate voice activity. If this count exceedsa threshold percentage or number of frames, the VAD 765 may beconfigured to output a signal or set a state variable indicating thatvoice activity is present in the environment. Other metrics may be usedas well in addition to, or as an alternative to, such a count.

The presence of voice activity in an environment may indicate that avoice input is being directed to the NMD 703. Accordingly, when the VAD765 indicates that voice activity is not present in the environment(perhaps as indicated by a state variable set by the VAD 765) this maybe configured as one of the command conditions for the local keywords.When this condition is met (i.e., the VAD 765 indicates that voiceactivity is present in the environment), the state machine 779 a willtransition to the first state to enable performing commands based onlocal keywords, so long as any other conditions for a particular localkeyword are satisfied.

Further, in some implementations, the NMD 703 may include a noiseclassifier 766. The noise classifier 766 is configured to determinesound metadata (frequency response, signal levels, etc.) and identifysignatures in the sound metadata corresponding to various noise sources.The noise classifier 766 may include a neural network or othermathematical model configured to identify different types of noise indetected sound data or metadata. One classification of noise may bespeech (e.g., far-field speech). Another classification, may be aspecific type of speech, such as background speech, and example of whichis described in greater detail with reference to FIG. 8. Backgroundspeech may be differentiated from other types of voice-like activity,such as more general voice activity (e.g., cadence, pauses, or othercharacteristics) of voice-like activity detected by the VAD 765.

For example, analyzing the sound metadata can include comparing one ormore features of the sound metadata with known noise reference values ora sample population data with known noise. For example, any features ofthe sound metadata such as signal levels, frequency response spectra,etc. can be compared with noise reference values or values collected andaveraged over a sample population. In some examples, analyzing the soundmetadata includes projecting the frequency response spectrum onto aneigenspace corresponding to aggregated frequency response spectra from apopulation of NMDs. Further, projecting the frequency response spectrumonto an eigenspace can be performed as a pre-processing step tofacilitate downstream classification.

In various embodiments, any number of different techniques forclassification of noise using the sound metadata can be used, forexample machine learning using decision trees, or Bayesian classifiers,neural networks, or any other classification techniques. Alternativelyor additionally, various clustering techniques may be used, for exampleK-Means clustering, mean-shift clustering, expectation-maximizationclustering, or any other suitable clustering technique. Techniques toclassify noise may include one or more techniques disclosed in U.S.application Ser. No. 16/227,308 filed Dec. 20, 2018, and titled“Optimization of Network Microphone Devices Using Noise Classification,”which is herein incorporated by reference in its entirety.

In some implementations, the additional buffer 769 (shown in dashedlines) may store information (e.g., metadata or the like) regarding thedetected sound S_(D) that was processed by the upstream AEC 763 andspatial processor 764. This additional buffer 769 may be referred to asa “sound metadata buffer.” Examples of such sound metadata include: (1)frequency response data, (2) echo return loss enhancement measures, (3)voice direction measures; (4) arbitration statistics; and/or (5) speechspectral data. In example implementations, the noise classifier 766 mayanalyze the sound metadata in the buffer 769 to classify noise in thedetected sound S_(D).

As noted above, one classification of sound may be background speech,such as speech indicative of far-field speech and/or speech indicativeof a conversation not involving the NMD 703. The noise classifier 766may output a signal and/or set a state variable indicating thatbackground speech is present in the environment. The presence of voiceactivity (i.e., speech) in the pre-roll portion of the voice input 780indicates that the voice input 780 might not be directed to the NMD 703,but instead be conversational speech within the environment. Forinstance, a household member might speak something like “our kids shouldhave a play date soon” without intending to direct the command keyword“play” to the NMD 703.

Further, when the noise classifier indicates that background speech ispresent is present in the environment, this condition may disable thelocal voice input pipeline 777. In some implementations, the conditionof background speech being absent in the environment (perhaps asindicated by a state variable set by the noise classifier 766) isconfigured as one of the command conditions for the command keywords.Accordingly, the state machine 779 a will not transition to the firststate when the noise classifier 766 indicates that background speech ispresent in the environment.

Further, the noise classifier 766 may determine whether backgroundspeech is present in the environment based on one or more metrics. Forexample, the noise classifier 766 may determine a count of frames in thepre-roll portion of the voice input 780 that indicate background speech.If this count exceeds a threshold percentage or number of frames, thenoise classifier 766 may be configured to output the signal or set thestate variable indicating that background speech is present in theenvironment. Other metrics may be used as well in addition to, or as analternative to, such a count.

Within example implementations, the NMD 703 a may support a plurality oflocal wake-words. To facilitate such support, the local wake-word engine771 may implement multiple identification algorithms corresponding torespective local wake-words. Yet further, the library 778 of the localNLU 776 may include a plurality of local keywords and be configured tosearch for text patterns corresponding to these command keywords in thesignal S_(ASR).

Referring still to FIG. 7B, in example embodiments, the VAS wake-wordengine 770 a and the local voice input pipeline 777 may take a varietyof forms. For example, the VAS wake-word engine 770 a and the localvoice input pipeline 777 may take the form of one or more modules thatare stored in memory of the NMD 703 (e.g., the memory 713 of FIG. 7A).As another example, the VAS wake-word engine 770 a and the local voiceinput pipeline 777 may take the form of a general-purposes orspecial-purpose processor, or modules thereof. In this respect, thewake-word engine 770 a and local voice input pipeline 777 may be part ofthe same component of the NMD 703 or each of the wake-word engine 770 aand the local voice input pipeline 777 may take the form of a dedicatedcomponent. Other possibilities also exist.

In some implementations, voice input processing via a cloud-based VASand local voice input processing are concurrently enabled. A user mayspeak a local wake-word to invoke local processing of a voice input 780b via the local voice input pipeline 777. Notably, even in the secondmode, the NMD 703 may forego sending any data representing the detectedsound S_(D) (e.g., the messages M_(V)) to a VAS when processing a voiceinput 780 b including a local wake word. Rather, the voice input 780 bis processed locally using the local voice input pipeline 777.Accordingly, speaking a voice input 780 b (with a local keyword) to theNMD 703 may provide increased privacy relative to other NMDs thatprocess all voice inputs using a VAS.

As indicated above, some keywords in the library 778 of the local NLU776 correspond to parameters. These parameters may define to perform thecommand corresponding to a detected command keyword. When keywords arerecognized in the voice input 780, the command corresponding to thedetected command keyword is performed according to parameterscorresponding to the detected keywords.

For instance, an example voice input 780 may be “play music at lowvolume” with “play” being the command keyword portion (corresponding toa playback command) and “music at low volume” being the voice utteranceportion. When analyzing this voice input 780, the NLU 776 may recognizethat “low volume” is a keyword in its library 778 corresponding to aparameter representing a certain (low) volume level. Accordingly, theNLU 776 may determine an intent to play at this lower volume level.Then, when performing the playback command corresponding to “play,” thiscommand is performed according to the parameter representing a certainvolume level.

In a second example, another example voice input 780 may be “play myfavorites in the Kitchen” with “play” again being the command keywordportion (corresponding to a playback command) and “my favorites in theKitchen” as the voice utterance portion. When analyzing this voice input780, the NLU 776 may recognize that “favorites” and “Kitchen” matchkeywords in its library 778. In particular, “favorites” corresponds to afirst parameter representing particular audio content (i.e., aparticular playlist that includes a user's favorite audio tracks) while“Kitchen” corresponds to a second parameter representing a target forthe playback command (i.e., the kitchen 101 h zone. Accordingly, the NLU776 may determine an intent to play this particular playlist in thekitchen 101 h zone.

In a third example, a further example voice input 780 may be “volume up”with “volume” being the command keyword portion (corresponding to avolume adjustment command) and “up” being the voice utterance portion.When analyzing this voice input 780, the NLU 776 may recognize that “up”is a keyword in its library 778 corresponding to a parameterrepresenting a certain volume increase (e.g., a 10 point increase on a100 point volume scale). Accordingly, the NLU 776 may determine anintent to increase volume. Then, when performing the volume adjustmentcommand corresponding to “volume,” this command is performed accordingto the parameter representing the certain volume increase.

Other example voice inputs may relate to smart device commands. Forinstance, an example voice input 780 may be “turn on patio lights” with“turn on” being the command keyword portion (corresponding to a power oncommand) and “patio lights” being the voice utterance portion. Whenanalyzing this voice input 780, the NLU 776 may recognize that “patio”is a keyword in its library 778 corresponding to a first parameterrepresenting a target for the smart device command (i.e., the patio 101i zone) and “lights” is a keyword in its library 778 corresponding to asecond parameter representing certain class of smart device (i.e., smartillumination devices, or “smart lights”) in the patio 101 i zone.Accordingly, the NLU 776 may determine an intent to turn on smart lightsassociated with the patio 101 i zone. As another example, anotherexample voice input 780 may be “set temperature to 75” with “settemperature” being the command keyword portion (corresponding to athermostat adjustment command) and “to 75” being the voice utteranceportion. When analyzing this voice input 780, the NLU 776 may recognizethat “to 75” is a keyword in its library 778 corresponding to aparameter representing a setting for the thermostat adjustment command.Accordingly, the NLU 776 may determine an intent to set a smartthermostat to 75 degrees.

Within examples, certain command keywords are functionally linked to asubset of the keywords within the library 778 of the local NLU 776,which may hasten analysis. For instance, the command keyword “skip” maybe functionality linked to the keywords “forward” and “backward” andtheir cognates. Accordingly, when the command keyword “skip” is detectedin a given voice input 780, analyzing the voice utterance portion ofthat voice input 780 with the local NLU 776 may involve determiningwhether the voice input 780 includes any keywords that match thesefunctionally linked keywords (rather than determining whether the voiceinput 780 includes any keywords that match any keyword in the library778 of the local NLU 776). Since vastly fewer keywords are checked, thisanalysis is relatively quicker than a full search of the library 778. Bycontrast, a nonce VAS wake word such as “Alexa” provides no indicationas to the scope of the accompanying voice input.

Some commands may require one or more parameters, as such the commandkeyword alone does not provide enough information to perform thecorresponding command. For example, the command keyword “volume” mightrequire a parameter to specify a volume increase or decrease, as theintent of “volume” of volume alone is unclear. As another example, thecommand keyword “group” may require two or more parameters identifyingthe target devices to group.

Accordingly, in some example implementations, when a given localwake-word is detected in the voice input 780 by the local wake-wordengine 771, the local NLU 776 may determine whether the voice input 780includes keywords matching keywords in the library 778 corresponding tothe required parameters. If the voice input 780 does include keywordsmatching the required parameters, the NMD 703 a proceeds to perform thecommand (corresponding to the given command keyword) according to theparameters specified by the keywords.

However, if the voice input 780 does include keywords matching therequired parameters for the command, the NMD 703 a may prompt the userto provide the parameters. For instance, in a first example, the NMD 703a may play an audible prompt such as “I've heard a command, but I needmore information” or “Can I help you with something?” Alternatively, theNMD 703 a may send a prompt to a user's personal device via a controlapplication (e.g., the software components 132 c of the controldevice(s) 104).

In further examples, the NMD 703 a may play an audible prompt customizedto the detected command keyword. For instance, after detect a commandkeyword corresponding to a volume adjustment command (e.g., “volume”),the audible prompt may include a more specific request such as “Do youwant to adjust the volume up or down?” As another example, for agrouping command corresponding to the command keyword “group,” theaudible prompt may be “Which devices do you want to group?” Supportingsuch specific audible prompts may be made practicable by supporting arelatively limited number of command keywords (e.g., less than 100), butother implementations may support more command keywords with thetrade-off of requiring additional memory and processing capability.

Within additional examples, when a voice utterance portion does notinclude keywords corresponding to one or more required parameters, theNMD 703 a may perform the corresponding command according to one or moredefault parameters. For instance, if a playback command does not includekeywords indicating target playback devices 102 for playback, the NMD703 a may default to playback on the NMD 703 a itself (e.g., if the NMD703 a is implemented within a playback device 102) or to playback on oneor more associated playback devices 102 (e.g., playback devices 102 inthe same room or zone as the NMD 703 a). Further, in some examples, theuser may configure default parameters using a graphical user interface(e.g., user interface 430) or voice user interface. For example, if agrouping command does not specify the playback devices 102 to group, theNMD 703 a may default to instructing two or more pre-configured defaultplayback devices 102 to form a synchrony group. Default parameters maybe stored in data storage (e.g., the memory 112 b (FIG. 1F)) andaccessed when the NMD 703 a determines that keywords exclude certainparameters. Other examples are possible as well.

In some implementations, the NMD 703 a sends the voice input 780 to aVAS when the local NLU 776 is unable to process the voice input 780(e.g., when the local NLU is unable to find matches to keywords in thelibrary 778, or when the local NLU 776 has a low confidence score as tointent). In an example, to trigger sending the voice input 780, the NMD703 a may generate a bridging event, which causes the voice extractor773 to process the sound-data stream S_(D), as discussed above. That is,the NMD 703 a generates a bridging event to trigger the voice extractor773 without a VAS wake-word being detected by the VAS wake-word engine770 a (instead based on a command keyword in the voice input 780, aswell as the NLU 776 being unable to process the voice input 780).

Before sending the voice input 780 to the VAS (e.g., via the messagesM_(V)), the NMD 703 a may obtain confirmation from the user that theuser acquiesces to the voice input 780 being sent to the VAS. Forinstance, the NMD 703 a may play an audible prompt to send the voiceinput to a default or otherwise configured VAS, such as “I'm sorry, Ididn't understand that. May I ask Alexa?” In another example, the NMD703 a may play an audible prompt using a VAS voice (i.e., a voice thatis known to most users as being associated with a particular VAS), suchas “Can I help you with something?” In such examples, generation of thebridging event (and trigging of the voice extractor 773) is contingenton a second affirmative voice input 780 from the user.

Within certain example implementations, while in the first mode, thelocal NLU 776 may process the signal S_(ASR) without necessarily a localwake-word event being generated by the local wake-word engine 771 (i.e.,directly). That is, the automatic speech recognition 775 may beconfigured to perform automatic speech recognition on the sound-datastream S_(D), which the local NLU 776 processes for matching keywordswithout requiring a local wake-word event. If keywords in the voiceinput 780 are found to match keywords corresponding to a command(possibly with one or more keywords corresponding to one or moreparameters), the NMD 703 a performs the command according to the one ormore parameters.

Further, in such examples, the local NLU 776 may process the signalS_(ASR) directly only when certain conditions are met. In particular, insome embodiments, the local NLU 776 processes the signal S_(ASR) onlywhen the state machine 779 a is in the first state. The certainconditions may include a condition corresponding to no background speechin the environment. An indication of whether background speech ispresent in the environment may come from the noise classifier 766. Asnoted above, the noise classifier 766 may be configured to output asignal or set a state variable indicating that far-field speech ispresent in the environment. Further, another condition may correspond tovoice activity in the environment. The VAD 765 may be configured tooutput a signal or set a state variable indicating that voice activityis present in the environment. The prevalence of false positivedetection of commands with a direct processing approach may be mitigatedusing the conditions determined by the state machine 779 a.

IV. Example Offline Voice Control Scenarios

As noted above, the NMD 703 may perform local (“offline”) voice inputprocessing. Local voice input processing is especially helpful whenvoice input processing via a voice assistant service is unavailable,such as during set-up or when the VAS is unavailable. Under certaincircumstances, the NMD 703 may prompt a user for a voice input to beprocessed locally. FIGS. 8A, 8B, 8C, 8D, 8E, and 8F present example“conversations” between the NMD 703 and a user, which are initiated bythe NMD 703.

FIG. 8A shows an example conversation 881 between the NMD 703 and a user123. In this example, the conversation 881 is initiated by the NMD 703when the NMD 703 is in a set-up procedure, which may be initiated whenthe NMD 703 is first powered-on (or factory reset). Alternatively, theconversation 881 may be initiated by the user, perhaps via user input(e.g., a voice input of “Please set-up my device” or the like).

In some examples, the NMD 703 may detect an “unconfigured” condition andinitiate the conversation 881 based on this condition. Such a conditionmay be stored in a state variable, which may be checked during astart-up or boot sequence. If the state variable indicates anunconfigured state, the NMD 703 may initiate the conversation 881. Afterset-up, the state variable may be updated by the NMD 703 to“configured,” so that the conversation 881 is not initiated onsubsequent boot sequences.

The conversation 881 starts with the NMD 703 outputting an exampleaudible prompt 881 a, which asks the user 123 if they would like toset-up the NMD 703. The example audible prompt 881 a, and other audibleprompts described herein, may be pre-recorded and stored in data storageof the NMD 703 (e.g., the memory 713). Alternatively, such prompts maybe dynamically generated using text-to-speech conversion.

After outputting the audible prompt 881 a, the NMD 703 monitors inputfrom the microphones 722 for a voice input. In particular, the localwake word engine 771 may monitor the sound data stream S_(DS) for localwake words. Generally, since the audible prompt 881 a is a yes-or-noquestion, the scope of keywords may be narrowed, effectively becoming“yes” or “no” and their cognates (e.g., “sure”, “yep”, “nope” and thelike). After detecting one or more keywords in a voice input, the NMD703 determines an intent of the voice input. In this case, the user 123has provided a voice input 881 b representing an affirmative response.

Next in the conversation 881, the NMD 703 outputs another exampleaudible prompt 881 c, which asks the user 123 if they would like toset-up a voice assistant service. Here, the user 123 has provided avoice input 881 d indicating that they would like to set-up Alexa. Inthis example, the word “Alexa” operates as a keyword, which the localNLU 776 uses to determine that user's intent to set-up the Alexa voiceassistant service. Alternatively, if the user did not indicate aparticular voice assistant service, the NMD 703 may output an audibleprompt indicating supported voice assistant services.

To facilitate configuration of the Alexa voice assistant service, theNMD 703 outputs another example audible prompt 881 c, which asks theuser 123 for their Amazon user account. The user responds by providing avoice input 881 f indicating their Amazon email. In this example, theNMD 703 outputs another example audible prompt 881 g, which notifies theuser that the NMD 703 has found the Amazon account associated with theuser's 123 email address and prompts the user 123 if they would like tocontinue. Within examples, the NMD 703 may maintain or have access topreviously-provided account credentials (e.g., that were provided whensetting up another NMD 703 or another service that uses the samecredentials, such as Amazon Music). Alternatively, the NMD 703 mayprompt the user 123 for their password using an audible prompt.

In further examples, the NMD 703 may identify a user based on apreviously-provided “voice print” based on their unique voice. The voiceassistant service and/or the media playback system 100 may maintain orhave access to this voice print. When the user provides voice input tothe NMD 703, the NMD 703 may query voice assistant service for accountsmatching the user's voice, in an effort to find the user's particularaccount. If the voice assistant service finds a matching account, thevoice assistant service may provide the NMD 703 with the authenticationinformation. Further, the NMD 703 may output a user identification(e.g., email address) to confirm that the correct account wasidentified.

The conversation 881 continues with the user 123 providing a user input881 h indicating a response to the audible prompt 881 g. Since theresponse in the user input 881 h is affirmative, the NMD 703 configuresthe NMD 703 with the Alexa voice assistant service. The NMD 703 outputsanother example audible prompt 881 i, which notifies the user 123 thatthe Alexa voice assistant service is now set-up on the NMD 703.

FIG. 8B shows another example conversation 882 between the NMD 703 andthe user 123. In this example, the conversation 882 is initiated by theNMD 703 when the NMD 703 is in a set-up procedure, which may beinitiated when the NMD 703 is first powered-on (or factory reset).Alternatively, the conversation 882 may be initiated by the user,perhaps via user input (e.g., a voice input of “Please set-up my device”or the like).

The conversation 882 begins with the NMD 703 outputting an exampleaudible prompt 882 a, which asks the user 123 if they would like toset-up the NMD 703. After outputting the audible prompt 882 a, the NMD703 monitors input from the microphones 722 for a voice input. In thiscase, the user 123 has provided a voice input 882 b representing anaffirmative response.

Subsequently, in the conversation 882, the NMD 703 outputs anotherexample audible prompt 882 c, which asks the user 123 if they would liketo set-up a voice assistant service. Here, the user 123 has provided avoice input 882 d indicating that they would like to set-up the Googlevoice assistant service. In this example, the word “Google” operates asa keyword, which the local NLU 776 uses to determine that user's intentto set-up the Google voice assistant service.

After the NMD 703 determines that the intent of the voice input 882 d isto set-up the Google voice assistant service, the NMD 703 outputsanother example audible prompt 882 e, which directs the user 123 toprovide their credentials for their Google account via the Sonos app.Within examples, the NMD 703 may send instructions to a controlapplication on the control device 104 to display a control interfacethat includes one or more controls to facilitate entry of user accountcredentials for supported voice assistant services. Then, when the useropens the control application, the control interface is displayed andthe user can provide their account information via the one or morecontrols.

After receiving input data representing account information for the user123, the NMD 703 configures the Google VAS on the NMD 703. After theconfiguration is complete, the NMD 703 outputs an example audible prompt882 f, which indicates to the user 123 that the NMD 703 is configured todetect the Google wake-word (e.g., via the VAS wake-word engine 770 a(FIG. 7C)) and transmit voice inputs to the Google VAS. Within examples,the NMD 703 may facilitate setting up additional VAS(s), perhaps byprompting the user 123 to set up an additional VAS.

In some examples, the NMD 703 may also prompt the user 123 to enableconcurrent voice processing. As noted above, this may be referred to as“adopting” the local voice input engine 771. To illustrate, theconversation 882 continues with the NMD 703 outputting an exampleaudible prompt 881 g asking the user 123 if they would like to enablevoice processing. Since the user 123 has provided a voice input 881 hindicating that they would like to enable local voice processing, theNMD 703 enables local voice processing (e.g., via the local voice inputpipeline 777 (FIG. 7C)).

Enabling local voice input processing may involve transitioning thelocal voice input engine 771 from a first mode to a second mode (e.g.,from a set-up mode to an operating mode). Alternatively, the NMD 703 maydisable local voice input processing after setting up one or moreVAS(s). In this case, the local voice input engine 771 may remain in theset-up mode, which allows the local voice input engine 771 to assistwith further set-up or troubleshooting. For instance, the user 123 mayuse local voice input processing to set-up one or more additional voiceassistant services.

FIG. 8C shows an example conversation 883 between the NMD 703 and theuser 123. In this example, the conversation 883 is initiated by the NMD703 when the NMD 703 is in a set-up procedure, which may be initiatedwhen the NMD 703 is first powered-on (or factory reset). Alternatively,the conversation 883 may be initiated by the user, perhaps via userinput (e.g., a voice input of “Please set-up my device” or the like).

The conversation 883 begins with the NMD 703 outputting an exampleaudible prompt 883 a, which asks the user 123 if they would like toset-up the NMD 703. After outputting the audible prompt 883 a, the NMD703 monitors input from the microphones 722 for a voice input. In thiscase, the user 123 has provided a voice input 883 b representing anaffirmative response.

Subsequently, in the conversation 883, the NMD 703 outputs anotherexample audible prompt 883 c, which asks the user 123 if they would liketo set-up a voice assistant service. Here, the user 123 has provided avoice input 883 d indicating a negative response (i.e., that they wouldnot like to set-up a voice assistant service).

Based on the voice input 883 d indicating the negative response, the NMD703 outputs another example audible prompt 883 e, which asks the user ifthey would like to enable local voice processing instead. Here, the user123 has provided a voice input 883 f indicating an affirmative response(i.e., that they would like to set-up a local voice processing). Sincethe user 123 has provided a voice input 881 f indicating that they wouldlike to enable local voice processing, the NMD 703 enables local voiceprocessing (e.g., via the local voice input pipeline 777 (FIG. 7C)). Asnoted above, enabling local voice input processing may involvetransitioning the local voice input engine 771 from a first mode to asecond mode (e.g., from a set-up mode to an operating mode).

The conversation 883 continues with the NMD 703 outputting an exampleaudible prompt 883 g, which indicates that the NMD 703 is able tocustomize local voice processing and asks the user if they would like toproceed with such customization. Here, the user 123 has provided a voiceinput 883 h indicating an affirmative response (i.e., that they wouldlike to customize local voice processing). Based on the voice input 883h, the NMD 703 may customize the keyword library 778 of the local NLU776 with keywords unique to the user 123. The conversation 883 continueswith the NMD 703 outputting an example audible prompt 883 i, whichindicates that the NMD 703 has set-up local voice processing on the NMD703.

FIG. 8D shows an example conversation 884 between the NMD 703 and theuser 123. In this example, the conversation 884 is initiated by the user123 with a voice input 884 a, which includes a query to the Amazon VASasking for the weather. Generally, the VAS wake-word engine 770 a willdetect the wake word “Alexa” and generate a VAS wake-word event totransmit the voice input 884 a to the Amazon VAS for processing.However, in this example, the NMD 703 detects an issue communicatingwith the Amazon VAS. For instance, the NMD 703 may attempt to transmitdata representing the voice input 884 a to a server of the Amazon VASand then fail to receive a response or acknowledgment.

The conversation 884 continues with the NMD 703 outputting an audibleprompt 884 b, which indicates that the NMD 703 has detected an issuewith processing the voice input 884 a with the Amazon VAS and asks theuser 123 if they would like to troubleshoot. Since the voice input 884 cincludes an affirmative response, the NMD 703 performs one or moretroubleshooting operations.

Example troubleshooting operations may include testing the Internetconnection (e.g., the connection between network router 109 (whichoperates as an Internet gateway for the LAN 111) and the networks 107(FIG. 1B)). The NMD 703 may test the home Internet connection by pingingone or more high-availability sites (e.g., one or more public DNSservers). If the NMD 703 receives a response from the pinged servers,the NMD 703 may assume that the Internet connection is working (and thatthe Amazon VAS failed to provide a response to the voice input 884 abecause of an issue with the VAS). On the other hand, if the NMD 703 isunable to receive a response from the pinged servers, the NMD 703 mayassume that the Internet connection is not working. Further exampletroubleshooting operations may involve determining whether other devicesare reachable on the LAN 111 (e.g., via pinging), such as the playbackdevices 102 and/or other NMDs 103.

In this example, the NMD 703 determines that the NMD 703 does not have aconnection to the Internet. As such, the conversation 884 continues withthe NMD 703 outputting an audible prompt 884 d indicating that the homeInternet connection appears to be down. Further the audible prompt 884 dindicates a possible troubleshooting step of resetting the router (e.g.,the network router 109) and asks for the user 123 to speak reset oncethis troubleshooting step has been performed. In other examples, the NMD703 may output audible prompts for the user 123 to perform othertroubleshooting steps and also to provide a specific voice inputindicating that the troubleshooting steps have been performed.

After the user 123 performs the troubleshooting step(s), the user 123provides a voice input 884 e indicating that the troubleshooting step(s)have been performed. The NMD 703 may then test the Internet connectionagain. In this example, the troubleshooting step has remedied the issue.As such, the NMD 703 outputs the audible prompt 884 f, which indicatesthat the Internet connection is back online. The user 123 then providesthe voice input 884 g for processing by the Amazon VAS.

In other examples, the NMD 703 may actively monitor for issues that mayinterfere with voice input processing. For instance, the NMD 703 maymonitor its Internet connection status and notify the user 123 if theInternet connection goes offline. FIG. 8E shows an example conversation885 between the NMD 703 and the user 123. In this example, theconversation 885 is initiated by the NMD 703 when the NMD 703 detectsthat its Internet connection is down. In particular, the NMD 703 outputsan audible prompt 885 a indicating that the Internet connection is downand asking the user 123 if they would like to troubleshoot.

Here, the user 123 provides a voice input 885 b, which includes anaffirmative response. Based on the voice input 885 b, the NMD 703performs one or more troubleshooting operations. In this example, theNMD 703 determines that the NMD 703 does not have a connection to theInternet. As such, the conversation 884 continues with the NMD 703outputting an audible prompt 885 c indicating that the home Internetconnection appears to be down. Further the audible prompt 885 cindicates a possible troubleshooting step of resetting the router (e.g.,the network router 109) and asks for the user 123 to speak reset oncethis troubleshooting step has been performed.

After the user 123 performs the troubleshooting step(s), the user 123provides a voice input 885 d indicating that the troubleshooting step(s)have been performed. The NMD 703 may then test the Internet connectionagain. In this example, the troubleshooting step has remedied the issue.As such, the NMD 703 outputs the audible prompt 885 e, which indicatesthat the Internet connection is back online.

In further examples, the NMD 703 may prompt the user to process a voiceinput locally when the VAS is unable to process the voice input. Toillustrate, FIG. 8F shows an example conversation 886 between the NMD703 and the user 123. In this example, the conversation 886 is initiatedby the user 123 with a voice input 886 a, which includes a request toplay music by the artist Courtney Barnett.

When the user provides the voice input 886 a, the VAS wake-word engine770 a will detect the wake word “Alexa” and generate a VAS wake-wordevent to transmit the voice input 886 a to the Amazon VAS forprocessing. However, in this example, the NMD 703 detects an issuecommunicating with the Amazon VAS. For instance, the NMD 703 may attemptto transmit data representing the voice input 886 a to a server of theAmazon VAS and then fail to receive a response or acknowledgment.

The conversation 886 continues with the NMD 703 outputting an audibleprompt 886 b. The audible prompt 886 b indicates that the NMD 703 hasdetected an issue with processing the voice input 886 a with the AmazonVAS and asks the user 123 if they would like to troubleshoot. Since thevoice input 886 c includes an affirmative response, the NMD 703 performsone or more troubleshooting operations.

In this example, the NMD 703 determines that the Amazon VAS is down orotherwise unavailable. Since the Amazon VAS is temporarily unable toprocess the voice input 886 a, the NMD 703 outputs an audible prompt 886d indicating that the Amazon VAS is unavailable and asking the user 123if they would like to process the voice input 886 a locally. Since thevoice input 886 e includes an affirmative response, the NMD 703processes the voice input locally and then provides a audible prompt 886f indicating that the command in the voice input 886 a was carried out.

Although conversions 881, 882, 883, 884, 885, and 886 have beendiscussed with respect to audible prompts and voice responses, otherexamples may utilize different types of notifications, as an alternativeto or concurrently with audible prompts. For instance, the mediaplayback system 100 may send push notifications to a user's controldevice 104. Such push notifications may include text to prompt the userto provide a voice input response or touch-input to the controllerinterfaces 540 on the control device 104.

In example implementations, the NMD 703 is paired with one or more smartdevices. FIG. 9 illustrates an example pairing arrangement between theNMD 703 and a smart device 902, which includes an integrated playbackdevice and smart illumination device. By pairing the NMD 703 with thesmart device(s), voice commands to control the smart device(s) may bedirected to the NMD 703 to control the smart device(s) withoutnecessarily including a keyword identifying the smart device(s) in thevoice command. For instance, commands such as “play back Better OblivionCommunity Center” and “turn on lights” are received by the NMD 703, butcarried out on the smart device 809 without necessarily identifying thesmart device 809 by name, room, zone, or the like. On the other hand, auser may still direct inputs to other smart devices in the MPS 100 byreferencing the name, room, zone, group, area, etc. that the smartdevice is associated with.

Within examples, a user may configure the pairing arrangement using agraphical user interface or voice user interface. For instance, the usermay use a GUI on a application of a control device 104 to configure thepairing arrangement. Alternatively, the user may speak a voice commandsuch as “Please pair with the Ikea® lamp” or “Please pair with theSonos® Play:1” to configure the pairing relationship. The NMD 703 maystore data representing the pairing arrangement in one or more statevariables, which may be referenced when identifying a device to carryout a voice command.

Further, in the exemplary pairing relationship of FIG. 9, the smartdevice 902 may play back audio responses to voice inputs. As notedabove, the NMD 703 may, in some examples, exclude audio playbackcomponents typically present in a playback device (e.g., audioprocessing components 216, amplifiers 217, and/or speakers 218) or mayinclude relatively less capable versions of these components. By pairingthe NMD 703 to a playback device, the playback device may provideplayback functions to complement the NMD, including playback of audioresponses to voice inputs captured by the NMD 703 and playback of audiocontent initiated via voice command to the NMD 703.

For instance, while in the second mode, the user may speak the voiceinput “Alexa, what is the weather,” which is captured by the microphones722 b (FIG. 7C) of the NMD 703. The NMD 703 transmits data representingthis voice input to the servers 106 a of the VAS 190. The servers 106 aprocess this voice input and provide data representing a spokenresponse. In some implementations, the smart device 902 receives thisdata directly from the computing devices 106 a of the VAS 190 via thenetworks 107 and the LAN 111. Alternatively, the NMD 703 may receive thedata from the VAS 190, but send the data to the smart device 902. Ineither case, the playback device 902 plays back the spoken response.

As noted above, in the second mode, voice input processing via the VAS190 and voice input processing via the local voice input pipeline 777may be concurrently enabled. In an example, a user may speak the voiceinput “Alexa, play ‘Hey Jude’ by the Beatles and turn on the Ikealamps.” Here, “Alexa” is an example of a VAS wake word and “Ikea” is anexample of a local keyword. Accordingly, such an input may generate botha VAS wake work event and a local keyword event on the NMD 703.

In some examples, the library 778 of the local NLU 776 is partiallycustomized to the individual user(s). In a first aspect, the library 778may be customized to the devices that are within the household of theNMD (e.g., the household within the environment 101 (FIG. 1A)). Forinstance, the library 778 of the local NLU may include keywordscorresponding to the names of the devices within the household, such asthe zone names of the playback devices 102 in the MPS 100. In a secondaspect, the library 778 may be customized to the users of the deviceswithin the household. For example, the library 778 of the local NLU 776may include keywords corresponding to names or other identifiers of auser's preferred playlists, artists, albums, and the like. Then, theuser may refer to these names or identifiers when directing voice inputsto the local voice input pipeline 777.

Within example implementations, the NMD 703 may populate the library 778of the local NLU 776 locally within the network 111 (FIG. 1B). As notedabove, the NMD 703 may maintain or have access to state variablesindicating the respective states of devices connected to the network 111(e.g., the playback devices 104). These state variables may includenames of the various devices. For instance, the kitchen 101 h mayinclude the playback device 101 b, which are assigned the zone name“Kitchen.” The NMD 703 may read these names from the state variables andinclude them in the library 778 of the local NLU 776 by training thelocal NLU 776 to recognize them as keywords. The keyword entry for agiven name may then be associated with the corresponding device in anassociated parameter (e.g., by an identifier of the device, such as aMAC address or IP address). The NMD 703 a can then use the parameters tocustomize control commands and direct the commands to a particulardevice.

In further examples, the NMD 703 may populate the library 778 bydiscovering devices connected to the network 111. For instance, the NMD703 a may transmit discovery requests via the network 111 according to aprotocol configured for device discovery, such as universalplug-and-play (UPnP) or zero-configuration networking. Devices on thenetwork 111 may then respond to the discovery requests and exchange datarepresenting the device names, identifiers, addresses and the like tofacilitate communication and control via the network 111. The NMD 703may read these names from the exchanged messages and include them in thelibrary 778 of the local NLU 776 by training the local NLU 776 torecognize them as keywords.

In further examples, the NMD 703 may populate the library 778 using thecloud. To illustrate, FIG. 10 is a schematic diagram of the MPS 100 anda cloud network 1002. The cloud network 1002 includes cloud servers1006, identified separately as media playback system control servers1006 a, streaming audio service servers 1006 b, and IOT cloud servers1006 c. The streaming audio service servers 1006 b may represent cloudservers of different streaming audio services. Similarly, the IOT cloudservers 1006 c may represent cloud servers corresponding to differentcloud services supporting smart devices 1090 in the MPS 100. Smartdevices 1090 include smart illumination devices, smart thermostats,smart plugs, security cameras, doorbells, and the like.

Within examples, a user may link an account of the MPS 100 to an accountof an IOT service. For instance, an IOT manufacturer (such as IKEA®) mayoperate a cloud-based IOT service to facilitate cloud-based control oftheir IOT products using smartphone app, website portal, and the like.In connection with such linking, keywords associated with thecloud-based service and the IOT devices may be populated in the library778 of the local NLU 776. For instance, the library 778 may be populatedwith a nonce keyword (e.g., “Hey Ikea”). Further, the library 778 may bepopulated with names of various IOT devices, keyword commands forcontrolling the IOT devices, and keywords corresponding to parametersfor the commands.

One or more communication links 1003 a, 1003 b, and 1003 c (referred tohereinafter as “the links 1003”) communicatively couple the MPS 100 andthe cloud servers 1006. The links 1003 can include one or more wirednetworks and one or more wireless networks (e.g., the Internet).Further, similar to the network 111 (FIG. 1B), a network 1011communicatively couples the links 1003 and at least a portion of thedevices (e.g., one or more of the playback devices 102, NMDs 103,control devices 104, and/or smart devices 1090) of the MPS 100.

In some implementations, the media playback system control servers 1006a facilitate populating the library 778 of local NLU 776. In an example,the media playback system control servers 1006 a may receive datarepresenting a request to populate the library 778 of a local NLU 776from the NMD 703 a. Based on this request, the media playback systemcontrol servers 1006 a may communicate with the streaming audio serviceservers 1006 b and/or IOT cloud servers 1006 c to obtain keywordsspecific to the user.

In some examples, the media playback system control servers 1006 a mayutilize user accounts and/or user profiles in obtaining keywordsspecific to the user. As noted above, a user of the MPS 100 may set-up auser profile to define settings and other information within the MPS100. The user profile may then in turn be registered with user accountsof one or more streaming audio services to facilitate streaming audiofrom such services to the playback devices 102 of the MPS 100.

Through use of these registered streaming audio services, the streamingaudio service servers 1006 b may collect data indicating a user's savedor preferred playlists, artists, albums, tracks, and the like, eithervia usage history or via user input (e.g., via a user input designatinga media item as saved or a favorite). This data may be stored in adatabase on the streaming audio service servers 1006 b to facilitateproviding certain features of the streaming audio service to the user,such as custom playlists, recommendations, and similar features. Underappropriate conditions (e.g., after receiving user permission), thestreaming audio service servers 1006 b may share this data with themedia playback system control servers 1006 a over the links 1003 b.

Accordingly, within examples, the media playback system control servers1006 a may maintain or have access to data indicating a user's saved orpreferred playlists, artists, albums, tracks, genres, and the like. If auser has registered their user profile with multiple streaming audioservices, the saved data may include saved playlists, artists, albums,tracks, and the like from two or more streaming audio services. Further,the media playback system control servers 1006 a may develop a morecomplete understanding of the user's preferred playlists, artists,albums, tracks, and the like by aggregating data from the two or morestreaming audio services, as compared with a streaming audio servicethat only has access to data generated through use of its own service.

Moreover, in some implementations, in addition to the data shared fromthe streaming audio service servers 1006 b, the media playback systemcontrol servers 1006 a may collect usage data from the MPS 100 over thelinks 1003 a, after receiving user permission. This may include dataindicating a user's saved or preferred media items on a zone basis.Different types of music may be preferred in different rooms. Forinstance, a user may prefer upbeat music in the Kitchen 101 h and moremellow music to assist with focus in the Office 101 e.

Using the data indicating a user's saved or preferred playlists,artists, albums, tracks, and the like, the media playback system controlservers 1006 a may identify names of playlists, artists, albums, tracks,and the like that the user is likely to refer to when providing playbackcommands to the NMDs 703 via voice input. Data representing these namescan then be transmitted via the links 1003 a and the network 1004 to theNMDs 703 and then added to the library 778 of the local NLU 776 askeywords. For instance, the media playback system control servers 1006 amay send instructions to the NMD 703 to include certain names askeywords in the library 778 of the local NLU 776. Alternatively, the NMD703 (or another device of the MPS 100) may identify names of playlists,artists, albums, tracks, and the like that the user is likely to referto when providing playback commands to the NMD 703 via voice input andthen include these names in the library 778 of the local NLU 776.

Due to such customization, similar voice inputs may result in differentoperations being performed when the voice input is processed by thelocal NLU 776 as compared with processing by a VAS. For instance, afirst voice input of “Alexa, play me my favorites in the Office” maytrigger a VAS wake-word event, as it includes a VAS wake word (“Alexa”).A second voice input of “Play me my favorites in the Office” may triggera command keyword, as it includes a command keyword (“play”).Accordingly, the first voice input is sent by the NMD 703 to the VAS,while the second voice input is processed by the local NLU 776.

While these voice inputs are nearly identical, they may cause differentoperations. In particular, the VAS may, to the best of its ability,determine a first playlist of audio tracks to add to a queue of theplayback device 102 f in the office 101 e. Similarly, the local NLU 776may recognize keywords “favorites” and “kitchen” in the second voiceinput. Accordingly, the NMD 703 performs the voice command of “play”with parameters of <favorites playlist> and <kitchen 101 h zone>, whichcauses a second playlist of audio tracks to be added to the queue of theplayback device 102 f in the office 101 e. However, the second playlistof audio tracks may include a more complete and/or more accuratecollection of the user's favorite audio tracks, as the second playlistof audio tracks may draw on data indicating a user's saved or preferredplaylists, artists, albums, and tracks from multiple streaming audioservices, and/or the usage data collected by the media playback systemcontrol servers 1006 a. In contrast, the VAS may draw on its relativelylimited conception of the user's saved or preferred playlists, artists,albums, and tracks when determining the first playlist.

A household may include multiple users. Two or more users may configuretheir own respective user profiles with the MPS 100. Each user profilemay have its own user accounts of one or more streaming audio servicesassociated with the respective user profile. Further, the media playbacksystem control servers 1006 a may maintain or have access to dataindicating each user's saved or preferred playlists, artists, albums,tracks, genres, and the like, which may be associated with the userprofile of that user.

In various examples, names corresponding to user profiles may bepopulated in the library 778 of the local NLU 776. This may facilitatereferring to a particular user's saved or preferred playlists, artists,albums, tracks, or genres. For instance, when a voice input of “PlayAnne's favorites on the patio” is processed by the local NLU 776, thelocal NLU 776 may determine that “Anne” matches a stored keywordcorresponding to a particular user. Then, when performing the playbackcommand corresponding to that voice input, the NMD 703 adds a playlistof that particular user's favorite audio tracks to the queue of theplayback device 102 c in the patio 101 i.

In some cases, a voice input might not include a keyword correspondingto a particular user, but multiple user profiles are configured with theMPS 100. In some cases, the NMD 703 a may determine the user profile touse in performing a command using voice recognition. Alternatively, theNMD 703 a may default to a certain user profile. Further, the NMD 703 amay use preferences from the multiple user profiles when performing acommand corresponding to a voice input that did not identify aparticular user profile. For instance, the NMD 703 a may determine afavorites playlist including preferred or saved audio tracks from eachuser profile registered with the MPS 100.

The IOT cloud servers 1006 c may be configured to provide supportingcloud services to the smart devices 1090. The smart devices 1090 mayinclude various “smart” internet-connected devices, such as lights,thermostats, cameras, security systems, appliances, and the like. Forinstance, an TOT cloud server 1006 c may provide a cloud servicesupporting a smart thermostat, which allows a user to control the smartthermostat over the internet via a smartphone app or web site.

Accordingly, within examples, the TOT cloud servers 1006 c may maintainor have access to data associated with a user's smart devices 1090, suchas device names, settings, and configuration. Under appropriateconditions (e.g., after receiving user permission), the IOT cloudservers 1006 c may share this data with the media playback systemcontrol servers 1006 a and/or the NMD 703 a via the links 1003 c. Forinstance, the IOT cloud servers 1006 c that provide the smart thermostatcloud service may provide data representing such keywords to the NMD703, which facilitates populating the library 778 of the local NLU 776with keywords corresponding to the temperature.

Yet further, in some cases, the IOT cloud servers 1006 c may alsoprovide keywords specific to control of their corresponding smartdevices 1090. For instance, the IOT cloud server 1006 c that providesthe cloud service supporting the smart thermostat may provide a set ofkeywords corresponding to voice control of a thermostat, such as“temperature,” “warmer,” or “cooler,” among other examples. Datarepresenting such keywords may be sent to the NMDs 703 over the links1003 and the network 1004 from the IOT cloud servers 1006 c.

As noted above, some households may include more than NMD 703. Inexample implementations, two or more NMDs 703 may synchronize orotherwise update the libraries of their respective local NLU 776. Forinstance, a first NMD 703 a and a second NMD 703 b may share datarepresenting the libraries of their respective local NLU 776, possiblyusing a network (e.g., the network 904). Such sharing may facilitate theNMDs 703 a being able to respond to voice input similarly, among otherpossible benefits.

In some embodiments, one or more of the components described above canoperate in conjunction with the microphones 720 to detect and store auser's voice profile, which may be associated with a user account of theMPS 100. In some embodiments, voice profiles may be stored as and/orcompared to variables stored in a set of command information or datatable. The voice profile may include aspects of the tone or frequency ofa user's voice and/or other unique aspects of the user, such as thosedescribed in previously-referenced U.S. patent application Ser. No.15/438,749.

In some embodiments, one or more of the components described above canoperate in conjunction with the microphones 720 to determine thelocation of a user in the home environment and/or relative to a locationof one or more of the NMDs 103. Techniques for determining the locationor proximity of a user may include one or more techniques disclosed inpreviously-referenced U.S. patent application Ser. No. 15/438,749, U.S.Pat. No. 9,084,058 filed Dec. 29, 2011, and titled “Sound FieldCalibration Using Listener Localization,” and U.S. Pat. No. 8,965,033filed Aug. 31, 2012, and titled “Acoustic Optimization.” Each of theseapplications is herein incorporated by reference in its entirety.

FIGS. 11A, 11B, 11C, and 11D show exemplary input and output from theNMD 703 configured in accordance with aspects of the disclosure.

FIG. 11A illustrates a first scenario in which a wake-word engine of theNMD 703 is configured to detect four local wake-words (“play”, “stop”,“resume”, “Sonos”). The local NLU 776 (FIG. 7C) is disabled. In thisscenario, the user has spoken the voice input “Hey, Sonos” to the NMD703, which triggers a new recognition of one of the local wake-word.

Yet further, the VAD 765 and noise classifier 766 (FIG. 7C) haveanalyzed 150 frames of a pre-roll portion of the voice input. As shown,the VAD 765 has detected voice in 140 frames of the 150 pre-roll frames,which indicates that a voice input may be present in the detected sound.Further, the noise classifier 766 has detected ambient noise in 11frames, background speech in 127 frames, and fan noise in 12 frames. Inthis example, the noise classifier 766 is classifying the predominantnoise source in each frame. This indicates the presence of backgroundspeech. As a result, the NMD has determined not to trigger on thedetected local keyword “Sonos.”

FIG. 11B illustrates a second scenario in which the local voicewake-word engine 771 of the NMD 703 is configured to detect a localkeyword (“play”) as well as two cognates of that command keyword (“playsomething” and “play me a song”). The local NLU 776 is disabled. In thissecond scenario, the user has spoken the voice input “play something” tothe NMD 703, which triggers a new recognition of one of the localkeywords (e.g., a command keyword event).

Yet further, the VAD 765 and noise classifier 766 have analyzed 150frames of a pre-roll portion of the voice input. As shown, the VAD 765has detected voice in 87 frames of the 150 pre-roll frames, whichindicates that a voice input may be present in the detected sound.Further, the noise classifier 766 has detected ambient noise in 18frames, background speech in 8 frames, and fan noise in 124 frames. Thisindicates that background speech is not present. Given the foregoing,the NMD 703 has determined to trigger on the detected local keyword“play.”

FIG. 11C illustrates a third scenario in which the local wake-wordengine 771 of the NMD 703 is configured to detect three local keywords(“play”, “stop”, and “resume”). The local NLU 776 is enabled. In thisthird scenario, the user has spoken the voice input “play Beatles in theKitchen” to the NMD 703, which triggers a new recognition of one of thelocal keywords (e.g., a command keyword event corresponding to play).

As shown, the ASR 775 has transcribed the voice input as “play beet lesin the kitchen.” Some error in performing ASR is expected (e.g., “beetles”). Here, the local NLU 776 has matched the keyword “beet les” to“The Beatles” in the local NLU library 778, which sets up this artist asa content parameter to the play command. Further, the local NLU 776 hasalso matched the keyword “kitchen” to “kitchen” in the local NLU library778, which sets up the kitchen zone as a target parameter to the playcommand. The local NLU produced a confidence score of0.63428231948273443 associated with the intent determination.

Here as well, the VAD 765 and noise classifier 766 have analyzed 150frames of a pre-roll portion of the voice input. As shown, the noiseclassifier 766 has detected ambient noise in 142 frames, backgroundspeech in 8 frames, and fan noise in 0 frames. This indicates thatbackground speech is not present. The VAD 765 has detected voice in 112frames of the 150 pre-roll frames, which indicates that a voice inputmay be present in the detected sound. Here, the NMD 703 has determinedto trigger on the detected command keyword “play.”

FIG. 11D illustrates a fourth scenario in which the local wake-wordengine 771 of the NMD is not configured to spot any local keywords.Rather, the local wake-word engine 771 will perform ASR and pass theoutput of the ASR to the local NLU 776. The local NLU 776 is enabled andconfigured to detect keywords corresponding to both commands andparameters. In the fourth scenario, the user has spoken the voice input“play some music in the Office” to the NMD 703.

As shown, the ASR 775 has transcribed the voice input as “lay some musicin the office.” Here, the local NLU 776 has matched the keyword “lay” to“play” in the local NLU library 778, which corresponds to a playbackcommand. Further, the local NLU 776 has also matched the keyword“office” to “office” in the local NLU library 778, which sets up theoffice 101 e zone as a target parameter to the play command. The localNLU 776 produced a confidence score of 0.14620494842529297 associatedwith the keyword matching. In some examples, this low confidence scoremay cause the NMD to not accept the voice input (e.g., if thisconfidence score is below a threshold, such as 0.5).

V. Example Offline Voice Control Techniques

FIG. 12 is a flow diagram showing an example method 1200 to performoffline voice processing. The method 1200 may be performed by anetworked microphone device, such as the NMD 703 (FIG. 7A).Alternatively, the method 1200 may be performed by any suitable deviceor by a system of devices, such as the playback devices 103, NMDs 103,control devices 104, computing devices 105, computing devices 106,and/or NMD 703.

Portions of the method 1200 may be performed during a set-up procedurefor the networked microphone device. For example, the set-up proceduremay include setting up a voice assistant service for use in processingvoice inputs received via the networked microphone device. The set-upprocedure may also include setting up local voice processing. Otherportions of the method 1200 may be performed when troubleshooting issuesthat arise during “normal” use (e.g., after the set-up procedure).

At block 1202, the method 1200 includes monitoring, via a local voiceinput pipeline, a sound data stream. For instance, while the local voiceinput pipeline 777 (FIG. 7C) is in a first mode (e.g., the exemplaryset-up mode discussed above), the local voice input pipeline 777 maymonitor the sound data stream S_(DS) from the microphones 722 forkeywords from the local keyword library 778 of the local NLU 776.

In some instances, the local voice input pipeline 777 may beginmonitoring for voice inputs during a set-up procedure for the NMD 703,perhaps after being powered-on and/or after prompting for input as towhether a user would like to set-up the NMD 703. For instance, asillustrated in FIG. 8A, the NMD 703 may output audible prompts 881 aand/or 881 c, which ask the user 123 if they would like to set-up theNMD 703 and further to set-up a voice assistant service on the NMD 703.In this example, the NMD 703 determines respective intents of the voiceinputs 881 b and 881 d, which represent a command to configure a voiceassistant service on the NMD 703. FIGS. 8B and 8C provide furtherexamples.

At block 1204, the method 1200 includes generating a local wake-wordevent corresponding to a first voice input. For example, the localwake-word engine 771 may generate a local wake-word event correspondingto a first voice input when the local wake-word engine 771 detects sounddata matching one or more particular local keywords in a first portionof the sound data stream S_(DS). For instance, the local wake-wordengine 771 may determine that the first voice input includes one or morelocal keywords that generate a local wake-word event, such as a noncelocal keyword (e.g., “Hey, Sonos”) and/or a command keyword.Alternatively, if the user was prompted for input (e.g., by way of a yesor no question), affirmative keywords (e.g., “yes” or “yeah”) ornegative keywords (e.g., “no”) may cause the local wake-word engine 771to generate a local wake-word event.

At block 1206, the method 1200 includes determining an intent based onone or more keywords in the first voice input. By way of example, thelocal NLU 776 (FIG. 7C) may determine an intent based on the one or moreparticular local keywords of the first voice input. In some instances,the determined intent represents a command to configure a voiceassistant service on the NMD 703.

In some cases, determined intent is contextual based on a prompt thatwas played back by the NMD 703. For instance, as shown in FIG. 8A, theNMD 703 outputs the audible prompt 881 a, which asks the user 123 ifthey would like to set-up the NMD 703. Here, the affirmative response inthe voice input 881 b (i.e., “Yes, please!”) represents a command toconfigure a voice assistant service on the NMD 703 because of thepreceding audible prompt 881 a.

At block 1208, the method 1200 includes outputting one or more audibleprompts to configure a VAS wake-word engine for one or more voiceassistant services. For instance, the NMD 703 may output, via at leastone speaker, one or more audible prompts to configure a VAS wake-wordengine for one or more voice assistant services based on the determinedintent representing a command to configure a voice assistant service onthe playback device. Example audible prompts include prompts to provideuser account credentials, as illustrated by the audible prompt 881 e(FIG. 8A), or to select a voice assistant service, such as the audibleprompt 882 c (FIG. 8B).

Other audible prompts to configure various aspects of a VAS arecontemplated as well. For instance, the NMD 703 may output an audibleprompt to configure a VAS wake-word engine for one or more voiceassistant services via a control application on a mobile device, asillustrated by the audible prompt 882 e (FIG. 8B). As another theaudible prompts may include a confirmation that a VAS is configured, asshown by the audible prompt 881 i (FIG. 8A) and the audible prompt 882 f(FIG. 8B).

Within examples, a user may provide instructions and/or information inresponse to the one or more audible prompts to configure the VASwake-word engine for one or more voice assistant services. The local NLU776 may determine an intent of these voice inputs, and proceedaccordingly with the set-up. Further, the NMD 703 uses the instructionsand/or information to configure the VAS wake-word engine(s) 770 for oneor more voice assistant services.

At block 1210, the method 1200 includes monitoring the sound data streamvia the VAS wake-word engine. The NMD 703 may begin monitoring the sounddata stream via the VAS wake-word engine during “normal use” (e.g.,after the above-mentioned set-up procedure). For instance, after the VASwake-word engine 770 a is configured for a particular voice assistantservice, the VAS wake-word engine 770 a may monitor the sound datastream S_(DS) from the microphones 722 for one or more VAS wake words ofthe particular voice assistant service. For instance, following theconversation 881 illustrated in FIG. 8A, the NMD 703 may monitor thesound data stream S_(DS) for VAS wake words of the Amazon Alexa VAS(e.g., “Alexa” or “Hey, Alexa,” among other examples).

At block 1212, the method 1200 includes generating a VAS wake-word eventcorresponding to a second voice input. For example, the VAS wake-wordengine 770 a may generate a VAS wake-word event corresponding to asecond voice input when the VAS wake-word engine detects sound datamatching a particular VAS wake word in a second portion of the sounddata stream S_(DS). As described in connection with FIG. 7C, when a VASwake word event is generated by the VAS wake-word engine 770 a, the NMD703 streams sound data representing a voice input to one or more serversof a voice assistant service. By way of example, referring to FIG. 8D,the VAS wake-word engine 770 a may generate a VAS wake-word event afterdetecting the VAS wake-word “Alexa” in the voice input 884 a.

At block 1214, the method 1200 includes detecting a failure by the voiceassistant service to provide a response to the second voice input. Forexample, the NMD 703 may attempt to stream sound data representing thesecond voice input to one or more servers of the VAS and be unable toestablish a connection. In another example, the NMD 703 may stream thestream sound data representing the second voice input to the VAS andthen not receive a response to the second voice input from the VAS. TheNMD 703 may detect these circumstances as failures by the voiceassistant service to provide a response to the second voice input.

Within example implementations, when the NMD 703 detects a failure, theNMD 703 performs one or more troubleshooting steps (perhaps afterreceiving user input representing a command to perform thetroubleshooting steps). The troubleshooting steps may include performingone or more Internet connection tests, such as testing the connection ofthe NMD 703 to the Internet. The troubleshooting steps may also includeother tests, depending on the type of failure detected.

In some cases, while performing the one or more Internet connectiontests, the NMD 703 may detect an Internet connection failure. Detectingthe Internet connection failure may involve determining that the NMD 703is disconnected from the Internet (e.g., by pinging a high-availabilityserver), which would indicate a client-side connection issue. Further,detecting the Internet connection failure may involve determining thatplayback device is connected to the Internet and the one or more serversof the particular VAS are inaccessible over the Internet from theplayback device such that the connection issue is on the server-side.

Based on detecting an Internet connection failure, the NMD 703 may playback one or more audible prompts related to the failure. For instance,the NMD 703 may play back an audible prompt indicating the detectedInternet connection failure. Additionally or alternatively, the NMD 703may play back a series of audible prompts to perform one or moreInternet connection troubleshooting actions corresponding to thedetected Internet connection failure

At block 1216, the method 1200 includes outputting one or more audibletroubleshooting prompts. For instance, the NMD 703 may output one ormore audible troubleshooting prompts indicating one or more issuescausing the failure. Additionally or alternatively, the NMD 703 mayoutput one or more audible troubleshooting prompts indicating one or oneor more troubleshooting actions to correct the one or more issuescausing the failure. To illustrate, the conversation 884 shown in FIG.8D includes audible troubleshooting prompts 884 b and 884 d. Asadditional examples, the conversation 885 (FIG. 8E) includes the audibletroubleshooting prompts 885 a and 885 c and the conversation 886 (FIG.8F) includes the audible troubleshooting prompts 886 b and 886 d.

At block 1218, the method 1200 includes monitoring the sound data streamvia the local voice input pipeline for voice input response(s) to theone or more audible troubleshooting prompts. For example, the localwake-word engine 771 may monitor the sound data stream S_(DS) from theone or more microphones 222 for voice input response(s) to the audibletroubleshooting prompt(s). By way of example, the conversation 884 ofFIG. 8D includes the voice input responses 884 c and 884 e. Asadditional examples, the conversation 885 (FIG. 8E) includes the voiceinput responses 885 b and 885 d and the conversation 886 (FIG. 8F)includes the voice input response 886 c.

At block 1220, the method 1200 includes determining intent(s) of thevoice input response(s) to the one more audible troubleshooting prompts.For instance, the local NLU 776 may determine intent(s) of the voiceinput response(s) to the one more audible troubleshooting prompts. Asnoted above, the determined intents may be contextual, based on apreceding audible prompt. For instance, the intents of the voice inputresponses 884 c and 884 e (FIG. 8D) are based on the preceding audibleprompts 884 b and 884 d, respectively.

At block 1222, the method 1200 includes performing one or moreoperations according to the determined intent of the voice inputresponse. For instance, the NMD 703 may perform one or moretroubleshooting steps (e.g., tests) to verify that the issue leading tothe failure is resolved. Further, the NMD 703 may output one or moreaudible prompts indicating that the issue is resolved (or that the issueis not yet resolved). To illustrate, the conversation 884 in FIG. 8Dincludes an audible prompt 884 f, which indicates that the Internetconnection is back online. The NMD 703 may output such a prompt afterperforming the Internet connection test(s) again in order to verify thatthe troubleshooting steps performed by the user 123 were successful.

In some implementations, the NMD 703 may process a voice input locallywhen a failure to process the voice input via the VAS is detected. Forinstance, the VAS wake-word engine 770 a may generate a VAS wake-wordevent corresponding to a third voice input and attempt to stream sounddata representing the third voice input to one or more servers of aparticular voice assistant service. Based on detecting the failure bythe particular voice assistant service to provide a response to thethird voice input, the local NLU 776 may determine an intent of thethird voice input and then the NMD 703 may output a response to thethird voice input that is based on the determined intent. Theconversation 886 (FIG. 8F) illustrates such an implementation.

In some cases, the NMD 703 may disable the VAS wake word engine(s) 770(e.g., based on user input). For instance, the NMD 703 may receive inputdata representing a command to disable the VAS wake-word engine(s) 770(e.g., via a voice input, such as voice input 883 d (FIG. 8C). Based onsuch an input, the NMD disables the VAS wake-word engine(s) 770.Disabling the VAS wake word engine may involve physically disconnectingthe VAS wake word engine from either the at least one microphone, thenetwork interface, or power, among other examples. When the VASwake-word engine(s) 770 are disabled, if the local wake-word engine 771detects a VAS wake word, the NMD 703 may output an audible promptindicating that the VAS wake-word engine is disabled.

As noted above, in some instances, the local voice input pipeline 777may initially operate in a first mode (i.e., a set-up mode) in which thelocal voice input engine 777 monitors the sound data stream S_(DS) for afirst (limited) set of keywords, which may generally include keywordsrelated to set-up. During the set-up procedure, the NMD 703 may receivedata representing instructions to configure the local voice inputpipeline 777 into an operating mode. The NMD 703 may receive theinstructions by voice input or via a network interface (e.g., from thecontrol device 104). To illustrate, the conversation 882 in FIG. 8Bincludes an audible prompt 882 g, which asks the user 123 if they wouldlike to enable local voice processing.

Based on receiving the data representing instructions to configure thelocal voice input engine 777 into the operating mode, the NMD 703switches the local voice input pipeline 777 from the set-up mode to anoperating mode. As discussed in connection with FIG. 7C, in theoperating mode, the local voice input engine 777 monitors the sound datastream for a second set of keywords from the local natural language unitlibrary 778. The second set comprises additional keywords relative tothe first set, such as keywords related to control of playback or othersmart devices.

In some implementations, the NMD 703 may prompt the user to enable thelocal voice input pipeline 777 during the set-up procedure. Theconversation 882 (FIG. 8B) and conversation 883 (FIG. 8C) includeexample audible prompts 882 g and 883 g to enable local voice inputprocessing. Further, as discussed in connection with FIG. 10, the localvoice input pipeline 777 may be customized by populating the localkeyword library 778 of the local NLU 776 with user-specific keywords.

During a voice control set-up procedure, the NMD 703 may play back anaudible prompt to retrieve user data from one or more cloud services,which the NMD 703 may use to customize the local keyword library 778 ofthe local NLU 776. For instance, the audible prompt 883 g asks the user123 if they permit such data to be accessed. After playing back theaudible prompt to retrieve user data from cloud services, the localvoice input pipeline 777 monitors the sound data stream S_(DS) from theone or more microphones 722 for a voice input response to the audibleprompt to retrieve user data from cloud services and then determines,via the local NLU 776, an intent of the voice input response to theaudible prompt to retrieve user data from cloud services. The voiceinput 883 h (FIG. 8C) provides an example of a voice input response thatrepresents an instruction to retrieve user data from the cloud services.

When the determined intent represents an instruction to retrieve userdata from the cloud services, the NMD 703 sends, to one or more cloudservices, instructions representing a request for data corresponding toone or more respective user accounts of the one or more cloud services.After sending the instructions, the NMD 703 receives data representingcorresponding to one or more respective user accounts of the one or morecloud services and configures the NMD 703 with the respective useraccounts of the one or more cloud services.

In some examples, the one or more cloud services include a streamingmedia service. In such examples, configuring the NMD 703 with therespective user accounts of the one or more cloud services may involvepopulating the local natural language unit library 778 of the local NLU776 with keywords corresponding to media particular to a user account(e.g., the user 123's user account). The keywords may include names ofplaylists associated with a particular user account, saved artistsassociated with the particular user account, saved albums associatedwith the particular user account, and/or saved audio tracks associatedwith the particular user account, among other examples, such as thosediscussed in connection with FIG. 10.

In further examples, the one or more cloud services include a smart homecloud service. In these examples, configuring the NMD 703 with therespective user accounts of the one or more cloud services may involvepopulating the local natural language unit library 778 of the local NLU776 with keywords corresponding to device names of smart devicesregistered with a particular user account of the smart home cloudservice and/or commands to control the smart devices registered with aparticular user account of the smart home cloud service. Other examplesare possible as well, such as those discussed in connection with FIG.10.

Within examples, the one or more cloud service include a media playbacksystem cloud service. In these examples, configuring the NMD 703 withthe respective user accounts of the one or more cloud services mayinvolve populating the local natural language unit library 778 of thelocal NLU 776 with keywords corresponding names of playback devices in amedia playback system and/or commands to control the playback devices inthe media playback system. As noted above, other examples are possibleas well, such as those discussed in connection with FIG. 10.

CONCLUSION

The description above discloses, among other things, various examplesystems, methods, apparatus, and articles of manufacture including,among other components, firmware and/or software executed on hardware.It is understood that such examples are merely illustrative and shouldnot be considered as limiting. For example, it is contemplated that anyor all of the firmware, hardware, and/or software aspects or componentscan be embodied exclusively in hardware, exclusively in software,exclusively in firmware, or in any combination of hardware, software,and/or firmware. Accordingly, the examples provided are not the onlyway(s) to implement such systems, methods, apparatus, and/or articles ofmanufacture.

The specification is presented largely in terms of illustrativeenvironments, systems, procedures, steps, logic blocks, processing, andother symbolic representations that directly or indirectly resemble theoperations of data processing devices coupled to networks. These processdescriptions and representations are typically used by those skilled inthe art to most effectively convey the substance of their work to othersskilled in the art. Numerous specific details are set forth to provide athorough understanding of the present disclosure. However, it isunderstood to those skilled in the art that certain embodiments of thepresent disclosure can be practiced without certain, specific details.In other instances, well known methods, procedures, components, andcircuitry have not been described in detail to avoid unnecessarilyobscuring aspects of the embodiments. Accordingly, the scope of thepresent disclosure is defined by the appended claims rather than theforgoing description of embodiments.

When any of the appended claims are read to cover a purely softwareand/or firmware implementation, at least one of the elements in at leastone example is hereby expressly defined to include a tangible,non-transitory medium such as a memory, DVD, CD, Blu-ray, and so on,storing the software and/or firmware.

The present technology is illustrated, for example, according to variousaspects described below. Various examples of aspects of the presenttechnology are described as numbered examples (1, 2, 3, etc.) forconvenience. These are provided as examples and do not limit the presenttechnology. It is noted that any of the dependent examples may becombined in any combination, and placed into a respective independentexample. The other examples can be presented in a similar manner.

Example 1

A method to be performed by a device including a network interface, oneor more microphones, one or more processors, at least one speaker, anddata storage having stored therein instructions executable by the one ormore processors. While a local voice input pipeline is in a set-up mode,the device monitors, via the local voice input pipeline, a sound datastream from the one or more microphones for local keywords from a localnatural language unit library of the local voice input pipeline. Thedevice generates a local wake-word event corresponding to a first voiceinput when the local voice input pipeline detects sound data matchingone or more particular local keywords in a first portion of the sounddata stream. The device determines, via a local natural language unit ofthe local voice input pipeline, an intent based on the one or moreparticular local keywords of the first voice input, the determinedintent representing a command to configure a voice assistant service onthe playback device. Based on the determined intent, the device outputs,via the at least one speaker, one or more audible prompts to configure aVAS wake-word engine for one or more voice assistant services. After theVAS wake-word engine is configured for a particular voice assistantservice, the device monitors, via the VAS wake-word engine, the sounddata stream from the one or more microphones for one or more VAS wakewords of the particular voice assistant service. The device generates aVAS wake-word event corresponding to a second voice input when the VASwake-word engine detects sound data matching a particular VAS wake wordin a second portion of the sound data stream, wherein, when the VAS wakeword event is generated, the playback device streams sound datarepresenting the second voice input to one or more servers of theparticular voice assistant service. The device detects a failure by theparticular voice assistant service to provide a response to the secondvoice input. Based on detecting the failure, the device outputs, via theat least one speaker, an audible troubleshooting prompt indicating atleast one of: (a) one or more issues causing the failure or (b) one ormore troubleshooting actions to correct the one or more issues causingthe failure. After playing back the audible troubleshooting prompt, thedevice monitors, via the local voice input pipeline, the sound datastream from the one or more microphones for a voice input response tothe audible troubleshooting prompt. The device determines, via the localnatural language unit, an intent of the voice input response to theaudible troubleshooting prompt and performs performing one or moreoperations according to the determined intent of the voice inputresponse to the audible troubleshooting prompt.

Example 2

The method of Example 1, wherein the one or more issues causing thefailure comprise an Internet connection issue, and wherein the methodfurther comprises: performing one or more Internet connection tests; andwhile performing the one or more Internet connection tests, detecting anInternet connection failure, wherein detecting the Internet connectionfailure comprises (a) determining that the playback device isdisconnected from the Internet or (b) determining (i) that playbackdevice is connected to the Internet and (ii) the one or more servers ofthe particular VAS are inaccessible over the Internet from the playbackdevice. The method further involves based on detecting an Internetconnection failure, playing back (i) an audible prompt indicating thedetected Internet connection failure and (ii) a series of audibleprompts to perform one or more Internet connection troubleshootingactions corresponding to the detected Internet connection failure.

Example 3

The method of any of Examples 1 and 2, wherein outputting the one ormore audible prompts to configure a VAS wake-word engine for one or morevoice assistant services comprises outputting an audible prompt toconfigure a VAS wake-word engine for one or more voice assistantservices via a control application on a mobile device.

Example 4

The method of any of Examples 1-3, wherein outputting the one or moreaudible prompts to configure a VAS wake-word engine for one or morevoice assistant services comprises outputting a series of audibleprompts to (i) select the particular voice assistant service from amonga plurality of voice assistant services supported by the playback deviceand (ii) provide user account information to register the playbackdevice with the particular voice assistant service.

Example 5

The method of any of Examples 4, wherein monitoring the first sound datastream for local keywords from the local natural language unit librarycomprises monitoring the first sound data stream for a first set ofkeywords from the local natural language unit library, and wherein themethod further comprises receiving data representing instructions toconfigure the local voice input pipeline into an operating mode andbased on receiving the data representing instructions to configure thelocal voice input pipeline into the operating mode, switching the localvoice input pipeline from the set-up mode to an operating mode, whereinin the operating mode, the local voice input pipeline monitors the sounddata stream for a second set of keywords from the local natural languageunit library, wherein the second set comprises additional keywordsrelative to the first set.

Example 6

The method of Example 5, further comprising: while the local voice inputpipeline is in the operating mode, monitoring, via the VAS wake-wordengine, the sound data stream from the one or more microphones for oneor more VAS wake words of the particular voice assistant service;generating a VAS wake-word event corresponding to a third voice inputwhen the VAS wake-word engine detects sound data matching a particularVAS wake word in a third portion of the sound data stream, wherein, whenthe VAS wake word event is generated, the playback device streams sounddata representing the third voice input to one or more servers of theparticular voice assistant service; detecting a failure by theparticular voice assistant service to provide a response to the thirdvoice input; based on detecting the failure by the particular voiceassistant service to provide a response to the third voice input,determining, via the local voice input pipeline, an intent of the thirdvoice input; and outputting, via the at least one speaker, a response tothe third voice input based on the determined intent.

Example 7

The method of any of Examples 1-6, further comprising: receiving inputdata representing a command to disable the VAS wake-word engine;disabling the VAS wake-word engine in response to receiving the inputdata representing the command to disable the VAS wake-word enginewherein disabling the VAS wake word engine comprises physicallydisconnecting the VAS wake word engine from one or more of: (a) the atleast one microphone, (b) the network interface, or (c) power; while theVAS wake-word engine is disabled, monitoring, via the local voice inputpipeline, the sound data stream from the one or more microphones for (a)the one or more VAS wake words and (b) local keywords; and when thelocal voice input pipeline detects sound data matching a given VAS wakeword in a given portion of the sound data stream, outputting, via the atleast one speaker, an audible prompt indicating that the VAS wake-wordengine is disabled.

Example 8

The method of Example 7, further comprising: generating a localwake-word event corresponding to a fourth voice input when the localvoice input pipeline detects sound data matching the given VAS wake wordin a fourth portion of the sound data stream; determining, via the localvoice input pipeline, an intent of the fourth voice input; andoutputting, via the at least one speaker, a response to the fourth voiceinput based on the determined intent.

Example 9

The method of any of Examples 1-8: further comprising: during a voicecontrol set-up procedure, playing back an audible prompt to retrieveuser data from one or more cloud services; after playing back theaudible prompt to retrieve user data from cloud services, monitoring thesound data stream from the one or more microphones for a voice inputresponse to the audible prompt to retrieve user data from cloudservices; determining, via the local natural language unit, an intent ofthe voice input response to the audible prompt to retrieve user datafrom cloud services; when the determined intent represents aninstruction to retrieve user data from the cloud services, sending, viathe network interface to one or more cloud services, instructionsrepresenting a request for data corresponding to one or more respectiveuser accounts of the one or more cloud services; receiving, via thenetwork interface, the data representing corresponding to one or morerespective user accounts of the one or more cloud services; andconfiguring the playback device with the respective user accounts of theone or more cloud services.

Example 10

The method of Example 9, wherein the one or more cloud services comprisea streaming media service, and wherein configuring the playback devicewith the respective user accounts of the one or more cloud servicescomprises: populating the local natural language unit library of thelocal voice input pipeline with keywords corresponding to at least oneof (i) playlists associated with a particular user account, (ii) savedartists associated with the particular user account, (iii) saved albumsassociated with the particular user account, and (iv) saved audio tracksassociated with the particular user account.

Example 11

The method of any of Examples 9-10, wherein the one or more cloudservices comprise a smart home cloud service, and wherein configuringthe playback device with the respective user accounts of the one or morecloud services comprises: populating the local natural language unitlibrary of the local voice input pipeline with keywords corresponding toat least one of (i) device names of smart devices registered with aparticular user account of the smart home cloud service and (ii)commands to control the smart devices registered with a particular useraccount of the smart home cloud service.

Example 12

The method of any of Examples 9-11: wherein the playback device is afirst playback device, wherein the one or more cloud service comprise amedia playback system cloud service, and wherein configuring theplayback device with the respective user accounts of the one or morecloud services comprises: populating the local natural language unitlibrary of the local voice input pipeline with keywords corresponding toat least one of (i) names of playback devices in a media playback systemthat comprises the first playback device and one or more second playbackdevices and (ii) commands to control the playback devices in the mediaplayback system.

Example 13

A tangible, non-transitory, computer-readable medium having instructionsstored thereon that are executable by one or more processors to cause aplayback device to perform the method of any one of Examples 1-12.

Example 14

A playback device comprising at least one speaker, a network interface,one or more microphones, one or more processors, and a data storagehaving instructions stored thereon that are executable by the one ormore processors to cause the playback device to perform the method ofany of Examples 1-12.

I claim:
 1. A playback device comprising: a network interface; one ormore microphones; at least one speaker; one or more processors; datastorage having instructions stored thereon that are executable by theone or more processors to cause the playback device to perform functionscomprising: while a local voice input pipeline is in a set-up mode,monitoring, via the local voice input pipeline, a sound data stream fromthe one or more microphones for local keywords from a local naturallanguage unit library of the local voice input pipeline; generating alocal wake-word event corresponding to a first voice input when thelocal voice input pipeline detects sound data matching one or moreparticular local keywords in a first portion of the sound data stream;determining, via a local natural language unit of the local voice inputpipeline, an intent based on the one or more particular local keywordsof the first voice input, the determined intent representing a commandto configure a voice assistant service on the playback device; based onthe determined intent, outputting, via the at least one speaker, one ormore audible prompts to configure a VAS wake-word engine for one or morevoice assistant services; after the VAS wake-word engine is configuredfor a particular voice assistant service, monitoring, via the VASwake-word engine, the sound data stream from the one or more microphonesfor one or more VAS wake words of the particular voice assistantservice; generating a VAS wake-word event corresponding to a secondvoice input when the VAS wake-word engine detects sound data matching aparticular VAS wake word in a second portion of the sound data stream,wherein, when the VAS wake word event is generated, the playback devicestreams sound data representing the second voice input to one or moreservers of the particular voice assistant service; detecting a failureby the particular voice assistant service to provide a response to thesecond voice input; based on detecting the failure, outputting, via theat least one speaker, an audible troubleshooting prompt indicating atleast one of: (a) one or more issues causing the failure or (b) one ormore troubleshooting actions to correct the one or more issues causingthe failure; after playing back the audible troubleshooting prompt,monitoring, via the local voice input pipeline, the sound data streamfrom the one or more microphones for a voice input response to theaudible troubleshooting prompt; determining, via the local naturallanguage unit, an intent of the voice input response to the audibletroubleshooting prompt; and performing one or more operations accordingto the determined intent of the voice input response to the audibletroubleshooting prompt.
 2. The playback device of claim 1, wherein theone or more issues causing the failure comprise an Internet connectionissue, and wherein the functions further comprise: performing one ormore Internet connection tests; while performing the one or moreInternet connection tests, detecting an Internet connection failure,wherein detecting the Internet connection failure comprises (a)determining that the playback device is disconnected from the Internetor (b) determining (i) that playback device is connected to the Internetand (ii) the one or more servers of the particular VAS are inaccessibleover the Internet from the playback device; and based on detecting anInternet connection failure, playing back (i) an audible promptindicating the detected Internet connection failure and (ii) a series ofaudible prompts to perform one or more Internet connectiontroubleshooting actions corresponding to the detected Internetconnection failure.
 3. The playback device of claim 1, whereinoutputting the one or more audible prompts to configure a VAS wake-wordengine for one or more voice assistant services comprises outputting anaudible prompt to configure a VAS wake-word engine for one or more voiceassistant services via a control application on a mobile device.
 4. Theplayback device of claim 1, wherein outputting the one or more audibleprompts to configure a VAS wake-word engine for one or more voiceassistant services comprises outputting a series of audible prompts to(i) select the particular voice assistant service from among a pluralityof voice assistant services supported by the playback device and (ii)provide user account information to register the playback device withthe particular voice assistant service.
 5. The playback device of claim1, wherein monitoring the first sound data stream for local keywordsfrom the local natural language unit library comprises monitoring thefirst sound data stream for a first set of keywords from the localnatural language unit library, and wherein the functions furthercomprise: receiving data representing instructions to configure thelocal voice input pipeline into an operating mode; and based onreceiving the data representing instructions to configure the localvoice input pipeline into the operating mode, switching the local voiceinput pipeline from the set-up mode to an operating mode, wherein in theoperating mode, the local voice input pipeline monitors the sound datastream for a second set of keywords from the local natural language unitlibrary, wherein the second set comprises additional keywords relativeto the first set.
 6. The playback device of claim 5, wherein thefunctions further comprise: while the local voice input pipeline is inthe operating mode, monitoring, via the VAS wake-word engine, the sounddata stream from the one or more microphones for one or more VAS wakewords of the particular voice assistant service; generating a VASwake-word event corresponding to a third voice input when the VASwake-word engine detects sound data matching a particular VAS wake wordin a third portion of the sound data stream, wherein, when the VAS wakeword event is generated, the playback device streams sound datarepresenting the third voice input to one or more servers of theparticular voice assistant service; detecting a failure by theparticular voice assistant service to provide a response to the thirdvoice input; based on detecting the failure by the particular voiceassistant service to provide a response to the third voice input,determining, via the local voice input pipeline, an intent of the thirdvoice input; and outputting, via the at least one speaker, a response tothe third voice input based on the determined intent.
 7. The playbackdevice of claim 1, wherein the functions further comprise: receivinginput data representing a command to disable the VAS wake-word engine;disabling the VAS wake-word engine in response to receiving the inputdata representing the command to disable the VAS wake-word enginewherein disabling the VAS wake word engine comprises physicallydisconnecting the VAS wake word engine from one or more of: (a) the oneor more microphones, (b) the network interface, or (c) power; while theVAS wake-word engine is disabled, monitoring, via the local voice inputpipeline, the sound data stream from the one or more microphones for (a)the one or more VAS wake words and (b) local keywords; and when thelocal voice input pipeline detects sound data matching a given VAS wakeword in a given portion of the sound data stream, outputting, via the atleast one speaker, an audible prompt indicating that the VAS wake-wordengine is disabled.
 8. The playback device of claim 7, wherein thefunctions further comprise: generating a local wake-word eventcorresponding to a fourth voice input when the local voice inputpipeline detects sound data matching the given VAS wake word in a fourthportion of the sound data stream; determining, via the local voice inputpipeline, an intent of the fourth voice input; and outputting, via theat least one speaker, a response to the fourth voice input based on thedetermined intent.
 9. The playback device of claim 1, wherein thefunctions further comprise: during a voice control set-up procedure,playing back an audible prompt to retrieve user data from one or morecloud services; after playing back the audible prompt to retrieve userdata from cloud services, monitoring the sound data stream from the oneor more microphones for a voice input response to the audible prompt toretrieve user data from cloud services; determining, via the localnatural language unit, an intent of the voice input response to theaudible prompt to retrieve user data from cloud services; when thedetermined intent represents an instruction to retrieve user data fromthe cloud services, sending, via the network interface to one or morecloud services, instructions representing a request for datacorresponding to one or more respective user accounts of the one or morecloud services; receiving, via the network interface, the datarepresenting corresponding to one or more respective user accounts ofthe one or more cloud services; and configuring the playback device withthe respective user accounts of the one or more cloud services.
 10. Theplayback device of claim 9, wherein the one or more cloud servicescomprise a streaming media service, and wherein configuring the playbackdevice with the respective user accounts of the one or more cloudservices comprises: populating the local natural language unit libraryof the local voice input pipeline with keywords corresponding to atleast one of (i) playlists associated with a particular user account,(ii) saved artists associated with the particular user account, (iii)saved albums associated with the particular user account, and (iv) savedaudio tracks associated with the particular user account.
 11. Theplayback device of claim 9, wherein the one or more cloud servicescomprise a smart home cloud service, and wherein configuring theplayback device with the respective user accounts of the one or morecloud services comprises: populating the local natural language unitlibrary of the local voice input pipeline with keywords corresponding toat least one of (i) device names of smart devices registered with aparticular user account of the smart home cloud service and (ii)commands to control the smart devices registered with a particular useraccount of the smart home cloud service.
 12. The playback device ofclaim 9, wherein the playback device is a first playback device, whereinthe one or more cloud service comprise a media playback system cloudservice, and wherein configuring the playback device with the respectiveuser accounts of the one or more cloud services comprises: populatingthe local natural language unit library of the local voice inputpipeline with keywords corresponding to at least one of (i) names ofplayback devices in a media playback system that comprises the firstplayback device and one or more second playback devices and (ii)commands to control the playback devices in the media playback system.13. A method to be performed by a playback device, the methodcomprising: while a local voice input pipeline is in a set-up mode,monitoring, via the local voice input pipeline, a sound data stream fromone or more microphones of the playback device for local keywords from alocal natural language unit library of the local voice input pipeline;generating a local wake-word event corresponding to a first voice inputwhen the local voice input pipeline detects sound data matching one ormore particular local keywords in a first portion of the sound datastream; determining, via a local natural language unit of the localvoice input pipeline, an intent based on the one or more particularlocal keywords of the first voice input, the determined intentrepresenting a command to configure a voice assistant service on theplayback device; based on the determined intent, outputting, via atleast one speaker, one or more audible prompts to configure a VASwake-word engine for one or more voice assistant services; after the VASwake-word engine is configured for a particular voice assistant service,monitoring, via the VAS wake-word engine, the sound data stream from theone or more microphones for one or more VAS wake words of the particularvoice assistant service; generating a VAS wake-word event correspondingto a second voice input when the VAS wake-word engine detects sound datamatching a particular VAS wake word in a second portion of the sounddata stream, wherein, when the VAS wake word event is generated, theplayback device streams sound data representing the second voice inputto one or more servers of the particular voice assistant service;detecting a failure by the particular voice assistant service to providea response to the second voice input; based on detecting the failure,outputting, via the at least one speaker, an audible troubleshootingprompt indicating at least one of: (a) one or more issues causing thefailure or (b) one or more troubleshooting actions to correct the one ormore issues causing the failure; after playing back the audibletroubleshooting prompt, monitoring, via the local voice input pipeline,the sound data stream from the one or more microphones for a voice inputresponse to the audible troubleshooting prompt; determining, via thelocal natural language unit, an intent of the voice input response tothe audible troubleshooting prompt; and performing one or moreoperations according to the determined intent of the voice inputresponse to the audible troubleshooting prompt.
 14. The method of claim13, wherein the one or more issues causing the failure comprise anInternet connection issue, and wherein the method further comprises:performing one or more Internet connection tests; while performing theone or more Internet connection tests, detecting an Internet connectionfailure, wherein detecting the Internet connection failure comprises (a)determining that the playback device is disconnected from the Internetor (b) determining (i) that playback device is connected to the Internetand (ii) the one or more servers of the particular VAS are inaccessibleover the Internet from the playback device; and based on detecting anInternet connection failure, playing back (i) an audible promptindicating the detected Internet connection failure and (ii) a series ofaudible prompts to perform one or more Internet connectiontroubleshooting actions corresponding to the detected Internetconnection failure.
 15. The method of claim 13, wherein outputting theone or more audible prompts to configure a VAS wake-word engine for oneor more voice assistant services comprises outputting an audible promptto configure a VAS wake-word engine for one or more voice assistantservices via a control application on a mobile device.
 16. The method ofclaim 13, wherein outputting the one or more audible prompts toconfigure a VAS wake-word engine for one or more voice assistantservices comprises outputting a series of audible prompts to (i) selectthe particular voice assistant service from among a plurality of voiceassistant services supported by the playback device and (ii) provideuser account information to register the playback device with theparticular voice assistant service.
 17. The method of claim 13, whereinmonitoring the first sound data stream for local keywords from the localnatural language unit library comprises monitoring the first sound datastream for a first set of keywords from the local natural language unitlibrary, and wherein the method further comprises: receiving datarepresenting instructions to configure the local voice input pipelineinto an operating mode; and based on receiving the data representinginstructions to configure the local voice input pipeline into theoperating mode, switching the local voice input pipeline from the set-upmode to an operating mode, wherein in the operating mode, the localvoice input pipeline monitors the sound data stream for a second set ofkeywords from the local natural language unit library, wherein thesecond set comprises additional keywords relative to the first set. 18.The method of claim 17, further comprising: while the local voice inputpipeline is in the operating mode, monitoring, via the VAS wake-wordengine, the sound data stream from the one or more microphones for oneor more VAS wake words of the particular voice assistant service;generating a VAS wake-word event corresponding to a third voice inputwhen the VAS wake-word engine detects sound data matching a particularVAS wake word in a third portion of the sound data stream, wherein, whenthe VAS wake word event is generated, the playback device streams sounddata representing the third voice input to one or more servers of theparticular voice assistant service; detecting a failure by theparticular voice assistant service to provide a response to the thirdvoice input; based on detecting the failure by the particular voiceassistant service to provide a response to the third voice input,determining, via the local voice input pipeline, an intent of the thirdvoice input; and outputting, via the at least one speaker, a response tothe third voice input based on the determined intent.
 19. The method ofclaim 13, further comprising: receiving input data representing acommand to disable the VAS wake-word engine; disabling the VAS wake-wordengine in response to receiving the input data representing the commandto disable the VAS wake-word engine wherein disabling the VAS wake wordengine comprises physically disconnecting the VAS wake word engine fromone or more of: (a) the one or more microphones, (b) a network interfaceof the playback device, or (c) power; while the VAS wake-word engine isdisabled, monitoring, via the local voice input pipeline, the sound datastream from the one or more microphones for (a) the one or more VAS wakewords and (b) local keywords; and when the local voice input pipelinedetects sound data matching a given VAS wake word in a given portion ofthe sound data stream, outputting, via the at least one speaker, anaudible prompt indicating that the VAS wake-word engine is disabled. 20.A tangible, non-transitory computer-readable medium storing instructionsthat, when executed by one or more processors of a playback device,cause the playback device to perform functions comprising: while a localvoice input pipeline is in a set-up mode, monitoring, via the localvoice input pipeline, a sound data stream from one or more microphonesof the playback device for local keywords from a local natural languageunit library of the local voice input pipeline; generating a localwake-word event corresponding to a first voice input when the localvoice input pipeline detects sound data matching one or more particularlocal keywords in a first portion of the sound data stream; determining,via a local natural language unit of the local voice input pipeline, anintent based on the one or more particular local keywords of the firstvoice input, the determined intent representing a command to configure avoice assistant service on the playback device; based on the determinedintent, outputting, via at least one speaker, one or more audibleprompts to configure a VAS wake-word engine for one or more voiceassistant services; after the VAS wake-word engine is configured for aparticular voice assistant service, monitoring, via the VAS wake-wordengine, the sound data stream from the one or more microphones for oneor more VAS wake words of the particular voice assistant service;generating a VAS wake-word event corresponding to a second voice inputwhen the VAS wake-word engine detects sound data matching a particularVAS wake word in a second portion of the sound data stream, wherein,when the VAS wake word event is generated, the playback device streamssound data representing the second voice input to one or more servers ofthe particular voice assistant service; detecting a failure by theparticular voice assistant service to provide a response to the secondvoice input; based on detecting the failure, outputting, via the atleast one speaker, an audible troubleshooting prompt indicating at leastone of: (a) one or more issues causing the failure or (b) one or moretroubleshooting actions to correct the one or more issues causing thefailure; after playing back the audible troubleshooting prompt,monitoring, via the local voice input pipeline, the sound data streamfrom the one or more microphones for a voice input response to theaudible troubleshooting prompt; determining, via the local naturallanguage unit, an intent of the voice input response to the audibletroubleshooting prompt; and performing one or more operations accordingto the determined intent of the voice input response to the audibletroubleshooting prompt.